New algorithms for improved speaker identification

Abstract

This paper focuses on developing new algorithms for improving speaker identification accuracy. Forty nine male speakers from the DARPA resource management continuous speech database were used for training and testing. Mel-frequency cepstral coefficients (MFCC) components were used for training and testing. Vector quantisation (VQ) was used for classification. In addition to presenting identification results, this paper shows the error reduction rate relative to a baseline system.