A Real-Time Audio Compression Technique Based on Fast Wavelet Filtering and Encoding

Abstract

Abstract-With the development of telecommunication technology over the last decades, the request for digital information compression has increased dramatically. In many applications, such as high quality audio transmission and storage, the target is to achieve audio and speech signal codings at the lowest possible data rates, in order to offer cheaper costs in terms of transmission and storage. Recently, compression techniques using wavelet transform have received great attention because of their promising compression ratio, signal to noise ratio, and flexibility in representing speech signals. In this paper we examine a new technique for analysing and compressing speech signals using biorthogonal wavelet filters. In particular, we compare this innovative compression method with a typical VoIP encoding of human voice, underlining how using wavelet filters may be convenient, mainly in terms of compression rate, without introducing a significant impairment in signal quality for listeners.

Comparison of communication performance of block coding methods in different channels using DWT

“…Table 1 summarises the parameters used in the simulation. In this study, (15,11) code size are used for all block coding types. Two sets of parameters are used for the simulation.…”

“…In [7], Haque et al studied the effect of various combined FEC codes on the performance of a wireless orthogonal frequency division multiplexing (OFDM) system. In this study, the authors used Reed-Solomon (RS) (255, 239, 8) encoder, Cyclic (15,11) encoder, Bose-Chaudhuri-Hocquenghem (BCH) (127, 64) encoder and ⅔ and ¾ encoders of convolutional coding for channel coding. QPSK, 8-PSK, 32-Quadrature Amplitude Modulation (32-QAM) and 64-QAM methods are used as the digital modulation method.…”

“…In the literature, wavelet transform (WT) is also used in some applications related to audio signal processing and channel coding. In [11], Romano et al proposed a technique for analysing and compressing speech signals using biorthogonal wavelet filters. This technique compared human voice with a typical voice over internet protocol (VoIP) encoding.…”

“…BPSK is preferred to use as the modulation type in our previous study and in this study since BPSK modulation generally showed better Eb/No versus BER performance than modulations such as QPSK, 4-QAM, 16-QAM, 64-QAM, 8-PSK and 16-PSK in studies [18][19][20][21][22][23]. In the second phase of the study, the AWGN, Rayleigh and Rician fading channels were individually coded with LBC (15,11), Hamming (15,11), Cyclic (15,11), BCH (15,11) and RS (15,11), respectively. Performance evaluation of these coding types was done with BER and mean squared error (MSE) criteria.…”

Linear Block Coding and Discrete Wavelet Transform Based Audio Signal Transmission over AWGN and Rician Fading Channels

“…In this study, the authors used Reed-Solomon (RS) (255, 239, 8) encoder, Cyclic (15,11) In the literature, Wavelet Transform (WT) is also used in some applications related to audio signal processing and channel coding. In [9], Romano et al proposed a technique for analyzing and compressing speech signals using biorthogonal wavelet filters. This technique compared human voice with a typical Voice Over Internet Protocol (VoIP) encoding.…”