Update app.py

app.py

@@ -15,7 +15,7 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 emotion_classifier = pipeline("text-classification",model='bhadresh-savani/distilbert-base-uncased-emotion')
 
-def translate(audio):
+def translate_and_classify(audio):
     
     print("""
     —
@@ -38,7 +38,9 @@ def translate(audio):
     print("Language Spoken: " + transcription.language)
     print("Transcript: " + transcription.text)  
     print("Translated: " + translation.text)
-        
+    
+    sentiment = emotion_classifier(translation.text)
+    
     return transcription.text
 
 with gr.Blocks() as demo:
@@ -48,7 +50,7 @@ with gr.Blocks() as demo:
     
     with gr.Row():
         with gr.Column():
-            gr.Markdown(""" ### Record audio """)
+            #gr.Markdown(""" ### Record audio """)
             audio_input = gr.Audio(label = 'Record Audio Input',source="microphone",type="filepath")
             with gr.Row():
                 transcribe_audio = gr.Button('Transcribe')