Speech compression using different transform techniques

Abstract

Speech Compression is a field of digital signal processing that focuses on reducing bit-rate of speech signals to enhance transmission speed and storage requirement of fast developing multimedia. This paper explores a transform based methodology for compression of the speech signal. In this methodology, different transforms such as Discrete Wavelet Transform (DWT), fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT) are exploited. A comparative study of performance of different transforms is made in terms of Signal-to-noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and Normalized root-mean square error (NRMSE). The simulation results included illustrate the effectiveness of these transforms in the field of data compression. When compared, Discrete Wavelet Transform gives higher compression respect to Discrete Cosine Transform and Fast Fourier Transform in terms of compression ratio, and DWT as well as good fidelity parameters also.