Optimal Spectral Resolution in Speaker Authentication Application in Noisy Environment and Telephony

Abstract

This article deals with the problem of speaker characterization, for which the principal interest is the improvement of the techniques of speaker authentication. For this purpose, we investigate the effect of spectral resolution in the speaker authentication performance. This investigation employs an approach based on the second order statistical measures using the Mel Frequency Spectral Coefficients (MFSC) and looks for the best spectral resolution. Experiments are done on microphonic and telephonic speech signals, with several MFSC dimensions and several types of noises. Results show the importance of the high spectral resolution in noisy environment and telephonic bandwidth, while the current research works have always favored the low resolution of 24 coefficients in such tasks. For example, we notice an improvement of about 11% on the identification score, since we increase the resolution from 24 to 48 MFSC, in the telephonic bandwidth.