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README.md
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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pipeline_tag: audio-to-audio
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metrics:
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- bleu
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library_name: transformers
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---
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- zh
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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- SparkAudio/Spark-TTS-0.5B
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- zai-org/glm-4-voice-tokenizer
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pipeline_tag: audio-to-audio
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metrics:
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- bleu
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library_name: transformers
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---
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# Model Card for UniSS
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## Model Details
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### Model Description
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UniSS is a unified single-stage speech-to-speech translation (S2ST) framework that achieves high translation fidelity and speech quality, while preserving timbre, emotion, and duration consistency.
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UniSS supports English and Chinese now.
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### Model Sources
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- **Repository:** https://github.com/cmots/UniSS
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- **Paper:**
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- **Demo:** https://cmots.github.io/uniss.github.io
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## Quick Start
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1. Install the environment
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```bash
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conda create -n uniss python=3.10.16
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conda activate uniss
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pip install uniss
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```
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2. Run the code
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``` python
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import soundfile
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from uniss import UniSSTokenizer
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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from uniss import process_input, process_output
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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wav_path = "prompt_audio.wav"
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model_path = "cmots/UniSS"
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# load the model, text tokenizer, and speech tokenizer
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model = AutoModelForCausalLM.from_pretrained(model_path)
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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speech_tokenizer = UniSSTokenizer.from_pretrained(model_path)
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# extract speech tokens
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glm4_tokens, bicodec_tokens = speech_tokenizer.tokenize(wav_path)
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tgt_lang = "<|eng|>"
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# process the input
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input_text = process_input(glm4_tokens, bicodec_tokens, "Quality", tgt_lang)
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# translate the speech
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output = model.generate(
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glm4_tokens,
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bicodec_tokens,
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max_new_tokens=100,
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num_beams=1,
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early_stopping=True,
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)
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output_text = tokenizer.decode(output, skip_special_tokens=True)
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audio, translation, transcription = process_output(output_text, input_text, speech_tokenizer, "Quality", device)
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soundfile.write("output_audio.wav", audio, 16000)
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print(translation)
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print(transcription)
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```
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## Citation
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```bibtex
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```
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