Mel Filter Bank energy-based Slope feature and its application to speaker recognition

Abstract

This paper investigates the use of Mel Filterbank Slope (MFS) feature for speaker recognition tasks. The Mel filterbank slope feature emphasises formants in comparison with that of the conventional Mel Filterbank Cepstral Coefficients (MFCC). The effectiveness of this feature is evaluated on the NIST 2003 speaker recognition database. Results show significant gain in performance on speaker identification accuracies by 8.9% and speaker verification EER by 1.6% with no additional computational costs involved. A combination of the MFS feature along with the delta MFCC feature shows further 2.7% and 1.2% improvements in the respective tasks. Late fusion on speaker verification systems are shown to give an overall improvement of 3%.