Update app.py

app.py

@@ -1,48 +1,22 @@
 import streamlit as st
-import speech_recognition as sr
 import whisper
-from io import BytesIO
 
-# Initialize recognizer
-recognizer = sr.Recognizer()
-
-# Function to capture audio using the microphone
-def capture_audio():
-    with sr.Microphone() as source:
-        st.write("Recording...")
-        audio = recognizer.listen(source)
-        st.write("Recording completed")
-        return audio
-
-# Convert speech to text using Whisper
-def transcribe_audio(audio):
-    audio_file = BytesIO(audio.get_wav_data())
+# Function to transcribe uploaded audio file
+def transcribe_audio(uploaded_file):
     model = whisper.load_model("base")
-    transcription = model.transcribe(audio_file)
+    transcription = model.transcribe(uploaded_file)
     return transcription['text']
 
 # Streamlit App Interface
-st.title("Real-time Speech Recognition App")
+st.title("Speech-to-Text Transcription")
 
-st.write("Click the button below to start recording.")
+st.write("Upload an audio file to get the transcription.")
 
-# Button to start recording
-if st.button("Start Recording"):
-    try:
-        audio_data = capture_audio()
-        st.write("Transcribing audio...")
-        transcription = transcribe_audio(audio_data)
-        st.write("Transcription:")
-        st.write(transcription)
-    except Exception as e:
-        st.write(f"An error occurred: {e}")
-
-# Optionally, provide an option to upload audio files
-uploaded_file = st.file_uploader("Or upload an audio file", type=["wav", "mp3", "ogg"])
+# Upload audio file
+uploaded_file = st.file_uploader("Upload an audio file", type=["wav", "mp3", "ogg"])
 
 if uploaded_file is not None:
-    st.write("Transcribing uploaded audio...")
-    model = whisper.load_model("base")
-    transcription = model.transcribe(uploaded_file)
+    st.write("Transcribing audio...")
+    transcription = transcribe_audio(uploaded_file)
     st.write("Transcription:")
-    st.write(transcription['text'])
+    st.write(transcription)