Gammachirp filterbank based speech analysis for speaker identification
Mouslem Bouchamekh, Boualem Bousseksou, Daoud Berkani · Computational intelligence · 2009
Many modern speaker recognition systems use a bank of linear filters as the first step in performing frequency analysis of speech and extracting the acoustics parameters that allow characterizing the speaker identity. In this paper we illustrate the use of novel feature set extracted from speech signal. The new technique for extracting these parameters is based on the human auditory system characteristics and relies on the gammachirp filterbank to emulate asymmetric frequency response and level dependent frequency response. For evaluation a comparative study was operated with standard MFCC.