Comparison of WT Based Speech Compression Techniques Using VC++

Abstract

The main purpose of this paper is to compresses the speech signal using wavelet transform. Psychoacoustics is the scientific study of sound perception. From the psychoacoustic point of view, we have selected Wavelet analysis for the digital speech compression. Also Wavelet Transform eliminates the irrelevancies and redundancies present in the speech signal. The two popoular models of Wavelet Transform for speech compression are-Filter bank model and Lifting Scheme.Filter Bank model is also called Subband Filtering model. Both  models decompose the speech signal into approximate and detailed components. But the lifting scheme is fast compared to the filtering model. We have tested some of the lifting scheme WT algorithms like Haar, Daubechies series, Cohen-Daubechies and Cohen-Daubechies-Feauveau bidirectionnel wavelet and have implemented them.