into wavelets coefficients at different scales and positions. These coefficients represent the signal in the wavelet domain and all data operations can be performed using just the corresponding wavelet coefficients. The major issues concerning the design of this Wavelet based speech coder are choosing optimal wavelets for speech signals, decomposition level in the DWT, thresholding criteria for coefficient truncation and efficient encoding of truncated coefficients. The
performance of the wavelet compression scheme on both male and female spoken sentences is compared. On a male spoken sentence the scheme reaches a signal-to-noise ratio of 17.45 db and a compression ratio of 3.88, using a level dependent thresholding
approach.