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import streamlit as st
import noisereduce as nr
import soundfile as sf
from pedalboard import NoiseGate, Compressor
import numpy as np
from io import BytesIO
# Function to remove background noise and process audio
def process_audio(input_file):
# Load the audio file
data, sr = sf.read(input_file)
# Reduce stationary noise using noisereduce
reduced_noise = nr.reduce_noise(y=data, sr=sr)
# Create a noise gate to further reduce noise using pedalboard
noise_gate = NoiseGate(threshold=0.02, attack=10, release=100)
# Create a compressor to enhance the audio
compressor = Compressor(threshold_db=-25, ratio=3,
attack_ms=10, release_ms=200)
# Create a pedalboard and add the noise gate and compressor to it
board = noise_gate >> compressor
# Process the audio through the pedalboard
processed_audio = board(np.array([reduced_noise]))
return processed_audio, sr
def main():
st.title("Background Noise Reduction")
# Upload audio file
uploaded_file = st.file_uploader("Upload audio file", type=["wav"])
if uploaded_file is not None:
# Process the audio
st.write("Processing audio...")
processed_audio, sr = process_audio(uploaded_file)
# Display processing progress
with st.spinner('Processing audio...'):
processed_audio_bytes = BytesIO()
sf.write(processed_audio_bytes,
processed_audio[0], sr, format='wav')
st.write("Audio processed successfully!")
# Allow user to play original and edited audio
st.subheader("Play Audio")
st.audio(uploaded_file, format='audio/wav',
start_time=0, caption='Original Audio')
st.audio(processed_audio_bytes, format='audio/wav',
start_time=0, caption='Processed Audio')
# Allow user to download processed audio
st.subheader("Download Processed Audio")
st.download_button("Download", processed_audio_bytes.getvalue(
), file_name="processed_audio.wav", mime='audio/wav')
if __name__ == "__main__":
main()
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