| Summary: | Wavelet Transform is a method that developed for analyzing the nonstationer
signal. Wavelet Transform was used in denoising process on speech to
enhance the quality of speech that courrupted by noise. The kinds of involved
noises are White Gaussian Noise (WGN), White Uniform Noise (WUN) dan
Colored Noise. In this research, the comparison of mother wavelet is performed
among Daubechies, Coiflet and Symlet in denoising process on speech. The
thresholding method that used in this denoising process is Soft Thresholding. The
threshold value is Time Adapted Threshold (TAT) that obtained by estimating the
power was used to generate the signal through Teager Energy Operator (TEO).
The kinds of tests that used for obtaining the best moher wavelet is Kruskal-
Wallis test and followed by Mann-Whitney test. The result shows that Db20,
Db30, Db40 and Coif5 mother wavelets are better than others to reduce WGN
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