Update app.py

app.py

@@ -12,7 +12,7 @@ def callback():
         st.audio(audio_bytes)
 
 def transcribe_and_translate(upload):
-    pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
+    pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")
     transcribe_result = pipe(upload, generate_kwargs={'task': 'transcribe'})
     translate_result = pipe(upload, generate_kwargs={'task': 'translate'})
     return transcribe_result['text'], translate_result['text']
@@ -82,19 +82,19 @@ def main():
         if options == "Start a recording":
             audio = mic_recorder(key='my_recorder', callback=callback)
         elif options == "Upload an audio":
-            audio = st.file_uploader("Please upload an audio")
+            audio = st.file_uploader("Please upload an audio", type=["wav", "mp3"])
         else:
             text = st.text_area("Please input the transcript (Only support English)")
         button = st.button('Submit')
 
     if button:
-        with st.spinner(text="Loading... It may take longer for initialisation."):
+        with st.spinner(text="Loading... It may take a while if you are running the app for the first time."):
             model, tokenizer = load_model()
             if options == "Start a recording":
                 transcibe_text, translate_text = transcribe_and_translate(upload=audio["bytes"])
                 prediction, probability = predict(text=translate_text, model=model, tokenizer=tokenizer)
             elif options == "Upload an audio":
-                transcibe_text, translate_text = transcribe_and_translate(upload=audio.getvalue)
+                transcibe_text, translate_text = transcribe_and_translate(upload=audio.getvalue())
                 prediction, probability = predict(text=translate_text, model=model, tokenizer=tokenizer)
             else:
                 transcibe_text = text
@@ -112,7 +112,7 @@ def main():
         # Convert probability to bar
         st.write(f'\n')
         objects = ('Hardware', 'Access', 'Miscellaneous', 'HR Support', 'Purchase', 'Administrative rights', 'Storage', 'Internal Project')
-        df = pd.DataFrame({'Categories': objects, 'Probability': probability[0]})
+        df = pd.DataFrame({'Categories': objects, 'Probability': np.around(probability[0])})
         st.bar_chart(data=df, x='Categories', y='Probability')
 
 if __name__ == '__main__':