Speech Enhancement using Maximal Overlap Discrete Wavelet Transform

Year 2018, Volume: 5 Issue: 4, 159 - 171, 30.12.2018

Selma Özaydın İman Khalil Alak

Abstract

Signal denoising for non-stationary digital signals can be effectively
succeeded by using discrete wavelet transform. Selecting of a suitable thresholding
method is important to minimize the loss of useful signal information. This
paper demonstrates the application of the maximal overlap wavelet transform
(Modwt) technique in speech signal denoising. The analysis algorithm was performed
on Matlab platform. In this algorithm, different kinds of input noisy speech signals
including environmental background noises such as restaurant, car, street or
station were tested. The noisy signals were filtered from the speech signal by thresholding
of wavelet coefficients with threshold estimation methods known as sgtwolog, modwtsqtwolog,
heursure, rigrsure and minimaxi. The performance of the Modwt in denoising
process was evaluated by comparing signal-to noise ratio (SNR) and mean square
error (MSE) results to those of well-known threshold estimation methods. First,
denoising effectiveness of a Modwt based threshold method was tested in
different scenarios and very important improvements in denoising process were
achieved by Modwt based scenarios. Next, the influence of the different
wavelets families on Modwt based threshold estimation method was evaluated by experimental
results. The results revealed that Modwt based method outperforms conventional threshold
methods while providing nearly up to a %24 increase in SNR value.

Keywords

wavelet thresholding, discrete wavelet transform, maximal overlap, speech enhancement

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