MATLAB Source Code for Speech Denoising Using Wavelet Transform-Based Speech Enhancement

In this article, we present a MATLAB source program for speech denoising using wavelet transform-based speech enhancement. This methodology enables users to effectively remove noise from audio signals, resulting in clearer speech output. We provide a detailed explanation of the MATLAB implementation process, including practical techniques for applying wavelet transforms to speech denoising tasks. The implementation typically involves several key steps: signal decomposition using wavelet families (such as Daubechies or Symlets), thresholding techniques (hard or soft thresholding) for noise reduction, and signal reconstruction from the processed wavelet coefficients. The code includes functions for wavelet decomposition (wavedec), threshold application (wthresh), and signal reconstruction (waverec). Additionally, we discuss potential application scenarios and analyze the advantages and limitations of this approach. The wavelet transform method excels in handling non-stationary signals and provides multi-resolution analysis, making it particularly suitable for speech signals with varying frequency characteristics. However, users should consider parameters like wavelet type, decomposition level, and threshold selection for optimal performance.