Update app.py

app.py

@@ -11,9 +11,7 @@ import torch
 import re
 import sys
 import soundfile as sf
-from utils import SpeechRecognition
-sp = SpeechRecognition()
-sp.load_model()
+
 
 
 
@@ -87,7 +85,7 @@ def predict_lang_specific(data,lang_code):
                 
     return decoded_results
 
-def recognition(audio_file):
+'''def recognition(audio_file):
     print("audio_file", audio_file.name)
     speech, rate = sp.load_speech_with_file(audio_file.name)
     
@@ -95,7 +93,7 @@ def recognition(audio_file):
     print(result)
 
     return result
-
+'''
 #predict(load_file_to_data('audio file path',sampling_rate=16_000)) # beware of the audio file sampling rate
 
 #predict_lang_specific(load_file_to_data('audio file path',sampling_rate=16_000),'en') # beware of the audio file sampling rate
@@ -115,11 +113,11 @@ with gr.Blocks() as demo:
         ]
         output_transcribe1 = gr.Textbox(label="output")
         transcribe_audio1= gr.Button("Submit")
-    with gr.Tab("Auto1"):
+    '''with gr.Tab("Auto1"):
         gr.Markdown("automatically detects your language")
         inputs_speech2 = gr.Audio(label="Input Audio", type="file")
         output_transcribe2 = gr.Textbox()
-        transcribe_audio2= gr.Button("Submit")
+        transcribe_audio2= gr.Button("Submit")'''
     transcribe_audio.click(fn=predict,
     inputs=inputs_speech,
     outputs=output_transcribe)
@@ -128,10 +126,9 @@ with gr.Blocks() as demo:
     inputs=inputs_speech1 ,
     outputs=output_transcribe1 )
     
-    transcribe_audio2.click(fn=recognition,
+    '''transcribe_audio2.click(fn=recognition,
     inputs=inputs_speech2 ,
-    outputs=output_transcribe2 )
-
+    outputs=output_transcribe2 )'''
 
 
 if __name__ == "__main__":