Speech Compression Based on Discrete Walsh Hadamard Transform

This paper presents a new lossy compression algorithm for stationary signal based on Discrete Walsh Hadamard Transform (DWHT). The principle of compression algorithm consists in framing the original speech signal into stationary frames and applying the DWHT. Then, the obtained coefficients are thresholded in order to truncate all coefficients below a given thresholds values. Compression is achieved by efficient encoding of the string values of zeros. A comparative study of performance between the algorithms based on DWHT and Discrete Wavelet Transform (DWT) is performed in terms of some objective criteria: compression ratio (CR), signal to noise ratio, peak signal to noise ratio (SNR), normalized root mean square error (NRMSE) and CPU time. The simulation results show that the algorithm based on DWHT is characterized by a very low complexity implementation and improved CR, SNR, PSNR and NRMSE compared to the DWT algorithm and this for stationary frame.