An Analysis and Comparative Evaluation of MFCC Variants for Speaker Identification over VoIP Networks

摘要

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.