Comparing speech compression using wavelets with other speech compression schemes

Speech compression is one area of digital signal processing that focuses on reducing the bit rate of the speech signal for transmission or storage without significant loss of quality. In recent years a new technique called wavelet transform has been proposed for signal analysis. It has been successfully used in image compression application. So far, less attention has been paid to the research in the speech compression using wavelet. This paper attempts to evaluate the wavelet compression technique on speech signals. Different wavelet filters were used to select the best filter suitable for speech signal in providing low bit rate and low computation complexity. Our implementation was evaluated based on PSNR, SNR, NRMSE and compression ratio tested on 8 kHz 8-bit speech signals. This algorithm was also compared to the following speech compression schemes: linear predictive coding (LPC) which reduces the transmitted data by factor of more than twelve, and global system mobile (GSM) which reduces the transmitted data by factor of five As a result from this study, wavelet speech compression gives higher SNR and better speech quality than the other techniques.