An analysis and comparative evaluation of MFCC variants for speaker identification over VoIP networks
Ayoub Bouziane, Jamal Kharroubi, Arsalane Zarghili · 2015
The aim of this paper is to evaluate, analyze and compare the performance of the most popular MFCC variants for features extraction in text-independent speaker identification over VoIP Networks. The MFCC variants were tested and evaluated under a Gaussian mixture model (GMM)-based speaker identification system, which represents the speaker modeling state-of-art approach in contemporary text-independent speaker identification systems.