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Create app.py
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app.py
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| 1 |
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import gradio as gr
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import torch
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import librosa
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from transformers import Wav2Vec2Processor, AutoModelForCTC
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import zipfile
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import os
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import firebase_admin
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from firebase_admin import credentials, firestore
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from datetime import datetime
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import json
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import tempfile
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# # Initialize Firebase
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# firebase_config = json.loads(os.environ.get('firebase_creds'))
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# cred = credentials.Certificate(firebase_config)
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# firebase_admin.initialize_app(cred)
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# db = firestore.client()
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# Load the ASR model and processor
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MODEL_NAME = "eleferrand/XLSR_Creole"
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processor = Wav2Vec2Processor.from_pretrained(MODEL_NAME)
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model = AutoModelForCTC.from_pretrained(MODEL_NAME)
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def transcribe(audio_file):
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try:
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audio, rate = librosa.load(audio_file, sr=16000)
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input_values = processor(audio, sampling_rate=16000, return_tensors="pt").input_values
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with torch.no_grad():
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logits = model(input_values).logits
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predicted_ids = torch.argmax(logits, dim=-1)
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transcription = processor.batch_decode(predicted_ids)[0]
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return transcription.replace("[UNK]", "")
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except Exception as e:
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return f"處理文件錯誤: {e}"
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def transcribe_both(audio_file):
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start_time = datetime.now()
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transcription = transcribe(audio_file)
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processing_time = (datetime.now() - start_time).total_seconds()
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return transcription, transcription, processing_time
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def store_correction(original_transcription, corrected_transcription, audio_file, age, native_speaker):
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try:
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audio_metadata = {}
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if audio_file and os.path.exists(audio_file):
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audio, sr = librosa.load(audio_file, sr=16000)
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duration = librosa.get_duration(y=audio, sr=sr)
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file_size = os.path.getsize(audio_file)
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audio_metadata = {'duration': duration, 'file_size': file_size}
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combined_data = {
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'original_text': original_transcription,
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'corrected_text': corrected_transcription,
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'timestamp': datetime.now().isoformat(),
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'audio_metadata': audio_metadata,
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'model_name': MODEL_NAME,
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'user_info': {
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'native_amis_speaker': native_speaker,
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'age': age
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}
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}
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db.collection('transcriptions').add(combined_data)
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return "校正保存成功! (Correction saved successfully!)"
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except Exception as e:
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return f"保存失败: {e} (Error saving correction: {e})"
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def prepare_download(audio_file, original_transcription, corrected_transcription):
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if audio_file is None:
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return None
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tmp_zip = tempfile.NamedTemporaryFile(delete=False, suffix=".zip")
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tmp_zip.close()
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with zipfile.ZipFile(tmp_zip.name, "w") as zf:
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if os.path.exists(audio_file):
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zf.write(audio_file, arcname="audio.wav")
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orig_txt = "original_transcription.txt"
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with open(orig_txt, "w", encoding="utf-8") as f:
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f.write(original_transcription)
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zf.write(orig_txt, arcname="original_transcription.txt")
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os.remove(orig_txt)
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corr_txt = "corrected_transcription.txt"
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with open(corr_txt, "w", encoding="utf-8") as f:
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f.write(corrected_transcription)
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zf.write(corr_txt, arcname="corrected_transcription.txt")
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os.remove(corr_txt)
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return tmp_zip.name
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def toggle_language(switch):
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"""Switch UI text between English and Traditional Chinese"""
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if switch:
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return (
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"阿美語轉錄與修正系統",
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"步驟 1:音訊上傳與轉錄",
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"步驟 2:審閱與編輯轉錄",
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"步驟 3:使用者資訊",
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"步驟 4:儲存與下載",
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"音訊輸入", "轉錄音訊",
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"原始轉錄", "更正轉錄",
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"年齡", "以阿美語為母語?",
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"儲存更正", "儲存狀態",
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"下載 ZIP 檔案"
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)
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else:
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return (
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"Amis ASR Transcription & Correction System",
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"Step 1: Audio Upload & Transcription",
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"Step 2: Review & Edit Transcription",
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"Step 3: User Information",
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"Step 4: Save & Download",
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"Audio Input", "Transcribe Audio",
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"Original Transcription", "Corrected Transcription",
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"Age", "Native Amis Speaker?",
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"Save Correction", "Save Status",
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"Download ZIP File"
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)
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# Interface
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# Interface
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with gr.Blocks() as demo:
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# lang_switch = gr.Checkbox(label="切換到繁體中文 (Switch to Traditional Chinese)")
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title = gr.Markdown("Yupik ASR Transcription & Correction System")
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step1 = gr.Markdown("Step 1: Audio Upload & Transcription")
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# Audio input and playback (Original section)
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with gr.Row():
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audio_input = gr.Audio(sources=["upload", "microphone"], type="filepath", label="Audio Input")
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step2 = gr.Markdown("Step 2: Review & Edit Transcription")
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# Transcribe button below the audio input (Added this section to place the button below the playback)
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with gr.Row(): # Added this Row to position the button below the audio input
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transcribe_button = gr.Button("Transcribe Audio")
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original_text = gr.Textbox(label="Original Transcription", interactive=False, lines=5)
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| 138 |
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corrected_text = gr.Textbox(label="Corrected Transcription", interactive=True, lines=5)
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step3 = gr.Markdown("Step 3: User Information")
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+
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with gr.Row():
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age_input = gr.Slider(minimum=0, maximum=100, step=1, label="Age", value=25)
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| 144 |
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native_speaker_input = gr.Checkbox(label="Native Yupik Speaker?", value=True)
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step4 = gr.Markdown("Step 4: Save & Download")
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| 147 |
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with gr.Row():
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save_button = gr.Button("Save Correction")
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| 150 |
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save_status = gr.Textbox(label="Save Status", interactive=False)
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| 151 |
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with gr.Row():
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download_button = gr.Button("Download ZIP File")
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| 154 |
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download_output = gr.File()
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+
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# Toggle language dynamically
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| 157 |
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# lang_switch.change(
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# toggle_language,
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| 159 |
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# inputs=lang_switch,
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| 160 |
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# outputs=[title, step1, step2, step3, step4, audio_input, transcribe_button,
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| 161 |
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# original_text, corrected_text, age_input, native_speaker_input,
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# save_button, save_status, download_button]
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# )
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| 164 |
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transcribe_button.click(
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transcribe_both,
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inputs=audio_input,
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outputs=[original_text, corrected_text]
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)
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| 170 |
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| 171 |
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save_button.click(
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store_correction,
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| 173 |
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inputs=[original_text, corrected_text, audio_input, age_input, native_speaker_input],
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| 174 |
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outputs=save_status
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| 175 |
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)
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| 177 |
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download_button.click(
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prepare_download,
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| 179 |
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inputs=[audio_input, original_text, corrected_text],
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| 180 |
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outputs=download_output
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| 181 |
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)
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+
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| 183 |
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demo.launch()
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