Upload app.py

app.py

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+import gradio as gr
+from transformers import pipeline, AutoModelForCTC, Wav2Vec2Processor, Wav2Vec2ProcessorWithLM
+
+MODELS = {
+    "Tatar": {"model_id": "sammy786/wav2vec2-xlsr-tatar", "has_lm": False},
+    "Chuvash": {"model_id": "sammy786/wav2vec2-xlsr-chuvash", "has_lm": False},
+    "Bashkir": {"model_id": "AigizK/wav2vec2-large-xls-r-300m-bashkir-cv7_opt", "has_lm": True},
+    "Erzya": {"model_id": "DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1", "has_lm": False}
+    }
+    
+CACHED_MODELS_BY_ID = {}
+    
+LANGUAGES_ENG = list(MODELS.keys())
+LANGUAGES_RUS = ["Татарский", "Чувашский", "Башкирский", "Эрзянский"]
+RUS2ENG = {k:v for k,v in zip(LANGUAGES_RUS, LANGUAGES_ENG)}
+LANG2YDX = {"Tatar": 'tt',
+    "Chuvash": "ba",
+    "Bashkir": "cv",
+    "Erzya": None,
+    "English": 'en',
+    'Русский': 'ru'
+}
+
+
+def run(input_file, language, decoding_type, lang):
+    language = RUS2ENG.get(language, language)
+    model = MODELS.get(language, None)
+    
+    model_instance = CACHED_MODELS_BY_ID.get(model["model_id"], None)
+    if model_instance is None:
+        model_instance = AutoModelForCTC.from_pretrained(model["model_id"])
+        CACHED_MODELS_BY_ID[model["model_id"]] = model_instance
+
+    if decoding_type == "LM":
+        processor = Wav2Vec2ProcessorWithLM.from_pretrained(model["model_id"])
+        asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer, 
+                        feature_extractor=processor.feature_extractor, decoder=processor.decoder)
+    else:
+        processor = Wav2Vec2Processor.from_pretrained(model["model_id"])
+        asr = pipeline("automatic-speech-recognition", model=model_instance, tokenizer=processor.tokenizer, 
+                        feature_extractor=processor.feature_extractor, decoder=None)
+
+    transcription = asr(input_file, chunk_length_s=5, stride_length_s=1)["text"]
+
+    if LANG2YDX[language]:
+      url = 'https://translate.yandex.ru/?lang=' + LANG2YDX[language] + '-' + LANG2YDX[lang] + '&text=' + transcription # ru-fr&text=
+      if lang == "Русский":
+        label = 'Посмотреть перевод'
+      else: label = 'Check the translation'
+      html = f'<a href="{url}"  target="_blank">{label}</a>'
+    else: html = None
+
+    return transcription, html
+    
+  
+def update_decoding(language):
+  language = RUS2ENG.get(language, language)
+  if MODELS[language]['has_lm']:
+    return gr.Radio.update(visible=True)
+  else: return gr.Radio.update(visible=False, value='Greedy')
+
+
+def update_interface(lang):
+  if lang == 'Русский':
+    languages = gr.Radio.update(label='Язык записи', choices=LANGUAGES_RUS)
+    audio =  gr.Audio.update(label='Скажите что-нибудь...')
+    # btn = gr.Button.update(value='Расшифровать')
+    decoding = gr.Radio.update(label='Тип декодирования')
+    
+  elif lang == 'English':
+    languages = gr.Radio.update(label='Language', choices=LANGUAGES_ENG)
+    audio = gr.Audio.update(label='Say something...')
+    # btn = gr.Button.update(value='Transcribe')
+    decoding = gr.Radio.update(label='Decoding type')
+
+  return languages, audio, decoding
+
+with gr.Blocks() as blocks:
+  lang = gr.Radio(label="Выберите язык интерфейса / Interface language", choices=['Русский','English'])
+  languages = gr.Radio(label="Language", choices=LANGUAGES_RUS)
+  audio = gr.Audio(source="microphone", type="filepath", label="Скажите что-нибудь...")
+  decoding = gr.Radio(label="Тип декодирования", choices=["Greedy", "LM"], visible=False, type='index')
+  btn = gr.Button('Расшифровать / Transcribe')
+  output = gr.Textbox(show_label=False)
+
+  translation = gr.HTML()
+  
+  languages.change(fn=update_decoding, inputs=[languages], outputs=[decoding])
+  lang.change(fn=update_interface, inputs=[lang], outputs=[languages, audio, decoding])
+  btn.click(fn=run, inputs=[audio, languages, decoding, lang], outputs=[output, translation])
+
+
+blocks.launch(enable_queue=True, debug=True)