Performance Evaluation of Text-Independent Speaker Identification and Verification Using MFCC and GMM

Palivela Hema
2012 IOSR Journal of Engineering  
This paper presents the performance of a text independent speaker identification and verification system using Gaussian Mixture Model(GMM).In this paper, we adapted Mel-Frequency Cepstral Coefficients(MFCC) as speaker speech feature parameters and the concept of Gaussian Mixture Model for classification with log-likelihood estimation. The Gaussian Mixture Modeling method with diagonal covariance is increasingly being used for both speaker identification and verification. We have used speakers
more » ... experiments, modeled with 13 mel-cepstral coefficients. Speaker verification performance was conducted using False Acceptance Rate (FAR), False Rejection Rate(FRR) and Equal Error Rate(ERR).
doi:10.9790/3021-02861822 fatcat:ipdby35whfhuvk7yyrbxcx3jsu