Update app.py

app.py

@@ -3,6 +3,7 @@ import torchaudio
 from torchaudio.transforms import Resample
 from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
 import streamlit as st
+from streamlit_audio_recorder import st_audio_recorder
 
 def preprocess_audio(audio_bytes, sample_rate=16000):
     # Load audio and convert to mono if necessary
@@ -33,14 +34,15 @@ def transcribe_audio(audio_bytes):
 
     return translation
 
-st.title("Audio to Text Transcription")
+st.title("Audio to Text Transcription with Recording")
 
-uploaded_file = st.file_uploader("Upload audio file", type=["wav"])
+# Use the st_audio_recorder widget to record audio
+audio_bytes = st_audio_recorder(sample_rate=16000, codec="wav", show_playback_controls=True)
 
-if uploaded_file is not None:
-    st.audio(uploaded_file, format="audio/wav")
+# Display the recorded audio
+if audio_bytes:
+    st.audio(audio_bytes, format="audio/wav")
 
-    audio_bytes = uploaded_file.getvalue()
     transcription = transcribe_audio(audio_bytes)
 
     if transcription:
@@ -49,5 +51,6 @@ if uploaded_file is not None:
     else:
         st.write("Error: Failed to transcribe audio.")
 else:
-    st.write("Please upload an audio file.")
+    st.write("Please record an audio.")  
+