Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 from transformers import pipeline
 from pydub import AudioSegment, silence
-import speech_recognition as sr
+#import speech_recognition as sr
 
 pipe = pipeline('sentiment-analysis')
 text = st.text_area('Enter your notes')
@@ -12,4 +12,12 @@ if text:
 
 st.markdown("<h1 style = text align:center;'> Group Therapy Notes </h1>",unsafe_allow_html = True)
 st.markdown("---",unsafe_allow_html=True)
-audio=st.file_uploader("Upload Your Audio File", type=['mp3','wav','m4a'])
+audio=st.file_uploader("Upload Your Audio File", type=['mp3','wav','m4a'])
+
+If audio:
+    audio_segment= AudioSegment.from_file(audio)
+    chunks=silence.split_on_silence(audio_segment, min_silence_length=500, silence_thresh= audio_segment.dBFs-20,keep_silence=100)
+    for index, chunk in enumerate (chunks):
+        chunk.export(str(index)+".wav", format="wav")
+        print(chunk)
+