A real-Time audio compression technique based on fast wavelet filtering and encoding

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.