mizoru commited on
Commit
1732531
1 Parent(s): dbc58cd

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +71 -41
app.py CHANGED
@@ -5,59 +5,89 @@ MODELS = {
5
  "Tatar": {"model_id": "sammy786/wav2vec2-xlsr-tatar", "has_lm": False},
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  "Chuvash": {"model_id": "sammy786/wav2vec2-xlsr-chuvash", "has_lm": False},
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  "Bashkir": {"model_id": "AigizK/wav2vec2-large-xls-r-300m-bashkir-cv7_opt", "has_lm": True},
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- "Erzya": {"model_id": "DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1", "has_lm": True}
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  }
10
 
11
  CACHED_MODELS_BY_ID = {}
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- LANGUAGES = list(MODELS.keys())
 
 
 
 
 
 
 
 
 
14
 
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- def run(input_file, language, decoding_type):
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-
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- #logger.info(f"Running ASR {language}-{model_size}-{decoding_type} for {input_file}")
18
 
 
 
19
  model = MODELS.get(language, None)
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-
21
 
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- if decoding_type == "LM" and not model["has_lm"]:
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- history.append({
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- "error_message": f"LM not available for {language} language :("
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- })
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- else:
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- # model_instance = AutoModelForCTC.from_pretrained(model["model_id"])
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- model_instance = CACHED_MODELS_BY_ID.get(model["model_id"], None)
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- if model_instance is None:
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- model_instance = AutoModelForCTC.from_pretrained(model["model_id"])
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- CACHED_MODELS_BY_ID[model["model_id"]] = model_instance
 
 
 
33
 
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- if decoding_type == "LM":
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- processor = Wav2Vec2ProcessorWithLM.from_pretrained(model["model_id"])
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- asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer,
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- feature_extractor=processor.feature_extractor, decoder=processor.decoder)
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- else:
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- processor = Wav2Vec2Processor.from_pretrained(model["model_id"])
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- asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer,
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- feature_extractor=processor.feature_extractor, decoder=None)
42
 
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- transcription = asr(input_file, chunk_length_s=5, stride_length_s=1)["text"]
 
 
 
 
 
 
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45
 
 
 
 
 
 
 
 
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- return transcription
 
 
 
 
 
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- gr.Interface(
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- run,
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- inputs=[
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- gr.Audio(source="microphone", type="filepath", label="Record something..."),
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- gr.Radio(label="Language", choices=LANGUAGES),
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- gr.Radio(label="Decoding type", choices=["greedy", "LM"])
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- # gr.inputs.Radio(label="Model size", choices=["300M", "1B"]),
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- ],
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- outputs=[
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- gr.Textbox()
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- ],
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- allow_screenshot=False,
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- allow_flagging="never",
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- theme="grass"
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- ).launch(enable_queue=True)
 
 
 
 
 
 
 
 
 
 
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  "Tatar": {"model_id": "sammy786/wav2vec2-xlsr-tatar", "has_lm": False},
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  "Chuvash": {"model_id": "sammy786/wav2vec2-xlsr-chuvash", "has_lm": False},
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  "Bashkir": {"model_id": "AigizK/wav2vec2-large-xls-r-300m-bashkir-cv7_opt", "has_lm": True},
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+ "Erzya": {"model_id": "DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1", "has_lm": False}
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  }
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  CACHED_MODELS_BY_ID = {}
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+ LANGUAGES_ENG = list(MODELS.keys())
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+ LANGUAGES_RUS = ["Татарский", "Чувашский", "Башкирский", "Эрзянский"]
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+ RUS2ENG = {k:v for k,v in zip(LANGUAGES_RUS, LANGUAGES_ENG)}
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+ LANG2YDX = {"Tatar": 'tt',
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+ "Chuvash": "ba",
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+ "Bashkir": "cv",
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+ "Erzya": None,
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+ "English": 'en',
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+ 'Русский': 'ru'
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+ }
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+ def run(input_file, language, decoding_type, lang):
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+ language = RUS2ENG.get(language, language)
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  model = MODELS.get(language, None)
 
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+ model_instance = CACHED_MODELS_BY_ID.get(model["model_id"], None)
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+ if model_instance is None:
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+ model_instance = AutoModelForCTC.from_pretrained(model["model_id"])
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+ CACHED_MODELS_BY_ID[model["model_id"]] = model_instance
 
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+ if decoding_type == "LM":
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+ processor = Wav2Vec2ProcessorWithLM.from_pretrained(model["model_id"])
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+ asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer,
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+ feature_extractor=processor.feature_extractor, decoder=processor.decoder)
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+ else:
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+ processor = Wav2Vec2Processor.from_pretrained(model["model_id"])
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+ asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer,
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+ feature_extractor=processor.feature_extractor, decoder=None)
42
 
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+ transcription = asr(input_file, chunk_length_s=5, stride_length_s=1)["text"]
 
 
 
 
 
 
 
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+ if LANG2YDX[language]:
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+ url = 'https://translate.yandex.ru/?lang=' + LANG2YDX[language] + '-' + LANG2YDX[lang] + '&text=' + transcription # ru-fr&text=
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+ if lang == "Русский":
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+ label = 'Посмотреть перевод'
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+ else: label = 'Check the translation'
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+ html = f'<a href="{url}" target="_blank">{label}</a>'
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+ else: html = None
52
 
53
+ return transcription, html
54
 
55
+
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+ def update_decoding(language):
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+ language = RUS2ENG.get(language, language)
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+ if MODELS[language]['has_lm']:
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+ return gr.Radio.update(visible=True)
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+ else: return gr.Radio.update(visible=False, value='Greedy')
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+
62
 
63
+ def update_interface(lang):
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+ if lang == 'Русский':
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+ languages = gr.Radio.update(label='Язык записи', choices=LANGUAGES_RUS)
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+ audio = gr.Audio.update(label='Скажите что-нибудь...')
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+ # btn = gr.Button.update(value='Расшифровать')
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+ decoding = gr.Radio.update(label='Тип декодирования')
69
 
70
+ elif lang == 'English':
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+ languages = gr.Radio.update(label='Language', choices=LANGUAGES_ENG)
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+ audio = gr.Audio.update(label='Say something...')
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+ # btn = gr.Button.update(value='Transcribe')
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+ decoding = gr.Radio.update(label='Decoding type')
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+
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+ return languages, audio, decoding
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+
78
+ with gr.Blocks() as blocks:
79
+ lang = gr.Radio(label="Выберите язык интерфейса / Interface language", choices=['Русский','English'])
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+ languages = gr.Radio(label="Language", choices=LANGUAGES_RUS)
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+ audio = gr.Audio(source="microphone", type="filepath", label="Скажите что-нибудь...")
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+ decoding = gr.Radio(label="Тип декодирования", choices=["Greedy", "LM"], visible=False, type='index')
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+ btn = gr.Button('Расшифровать / Transcribe')
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+ output = gr.Textbox(show_label=False)
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+
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+ translation = gr.HTML()
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+
88
+ languages.change(fn=update_decoding, inputs=[languages], outputs=[decoding])
89
+ lang.change(fn=update_interface, inputs=[lang], outputs=[languages, audio, decoding])
90
+ btn.click(fn=run, inputs=[audio, languages, decoding, lang], outputs=[output, translation])
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+
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+
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+ blocks.launch(enable_queue=True, debug=True)