Update app.py

app.py

@@ -18,43 +18,17 @@ from processDoubles import process_doubles
 from replaceWords import replace_words
 
 transcriber = pipeline(task="automatic-speech-recognition", model="cdactvm/w2v-bert-2.0-hindi_v1")
-# processor = AutoProcessor.from_pretrained("cdactvm/w2v-bert-2.0-hindi_v1")
 
-# vocab_dict = processor.tokenizer.get_vocab()
 
-# sorted_vocab_dict = {k.lower(): v for k, v in sorted(vocab_dict.items(), key=lambda item: item[1])}
-# decoder = build_ctcdecoder(
-#     labels=list(sorted_vocab_dict.keys()),
-#     kenlm_model_path="lm.binary",
-#     )
-# processor_with_lm = Wav2Vec2ProcessorWithLM(
-#     feature_extractor=processor.feature_extractor,
-#     tokenizer=processor.tokenizer,
-#     decoder=decoder
-#     )
-# processor.feature_extractor._processor_class = "Wav2Vec2ProcessorWithLM"
-
- 
 def transcribe(audio):
     # # Process the audio file
     transcript = transcriber(audio)
     text_value = transcript['text']
-    print(text_value)
     processd_doubles=process_doubles(text_value)
-    converted_to_list=convert_to_list(processd_doubles,text_to_list())
-    replaced_words = replace_words(converted_to_list)
+    replaced_words = replace_words(processd_doubles)
     converted_text=text_to_int(replaced_words)
     return converted_text
 
-
-# demo = gr.Interface(
-#     transcribe,
-#     gr.Audio(sources="microphone", type="filepath"),
-#     "text",
-# )
-
-# demo.launch()
-
 demo=gr.Interface(
     transcribe,
     inputs=[