Update app.py

app.py

@@ -1,45 +1,28 @@
 import streamlit as st
 import noisereduce as nr
-from pydub import AudioSegment
+import soundfile as sf
+import io
+import numpy as np
 
 # Define a Streamlit app
-st.title("Audio Processing App")
+st.title("Audio Noise Reduction App")
 
 # Upload the input audio file
 uploaded_audio = st.file_uploader("Upload an audio file", type=["mp3", "wav"])
 
 if uploaded_audio is not None:
-    # Load the input audio
-    audio = AudioSegment.from_file(uploaded_audio)
-
-    # Apply noise reduction using noisereduce
-    st.write("Applying noise reduction...")
+    audio_bytes = uploaded_audio.read()
     
-    # Convert audio to numpy array
-    audio_data = audio.get_array_of_samples()
-    reduced_audio_data = nr.reduce_noise(y=audio_data, sr=audio.frame_rate)
-
-    # Create a new AudioSegment from the reduced audio data
-    reduced_audio = AudioSegment(
-        reduced_audio_data.tobytes(),
-        frame_rate=audio.frame_rate,
-        sample_width=reduced_audio_data.dtype.itemsize,
-        channels=1  # Assuming mono audio
-    )
-
-    # Slow down the audio
-    st.write("Slowing down audio...")
-    slowed_audio = reduced_audio.speedup(playback_speed=0.7)  # Adjust the speed factor as needed
-
-    # Generate a new audio file
-    st.write("Generating output audio...")
-
-    # Export the slowed audio to a file
-    slowed_audio.export("output_audio.wav", format="wav")
+    # Convert audio file to numpy array
+    audio, sample_rate = sf.read(io.BytesIO(audio_bytes))
+    
+    # Apply noise reduction
+    st.write("Applying noise reduction...")
+    reduced_audio = nr.reduce_noise(y=audio, sr=sample_rate)
 
-    # Provide the download link for the processed audio
-    st.audio("output_audio.wav")
+    # Provide a link to download the processed audio
+    st.audio(reduced_audio, format="audio/wav")
 
 # Run the Streamlit app
 if __name__ == "__main__":
-    st.write("Upload an audio file to get started.")
+    st.write("Upload an audio file to apply noise reduction.")