Wavelet Denoising - Speech Signal Enhancement in Noisy Environments

The wavelet denoising MATLAB program is an effective signal processing method that enhances speech signal quality in noisy environments. This approach is applicable to various scenarios such as audio processing and speech recognition systems. In this implementation, the program processes imported audio files as the original speech signals, with additive Gaussian random noise simulated to represent real-world conditions. The algorithm employs the db3 wavelet basis for 1D discrete wavelet inverse transformation, where key steps include wavelet decomposition, threshold selection using methods like universal threshold or SURE threshold, and wavelet reconstruction. Through multi-resolution analysis, the program effectively separates noise components from the speech signal, significantly improving signal clarity and audibility. The implementation typically involves MATLAB's wavelet toolbox functions such as wdenoise for automated denoising or custom workflows using wavedec and waverec for precise control over decomposition levels and threshold parameters, ultimately delivering enhanced speech quality that better meets user requirements.