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#!/usr/bin/env python
# coding: utf-8
# In[1]:
# Function to apply wavelet denoising
def wavelet_denoise(audio, wavelet='db1', level=1):
coeffs = pywt.wavedec(audio, wavelet, mode='per')
# Thresholding detail coefficients
sigma = np.median(np.abs(coeffs[-level])) / 0.6745
uthresh = sigma * np.sqrt(2 * np.log(len(audio)))
coeffs[1:] = [pywt.threshold(i, value=uthresh, mode='soft') for i in coeffs[1:]]
return pywt.waverec(coeffs, wavelet, mode='per')
# In[ ]:
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