Automatic Talker Identification Using Optimal Spectral Resolution: Application in noisy environment and telephony

This chapter deals with the problem of speaker characterization, for which the principal interest is the improvement of the techniques of talker identification. For this purpose, the authors investigate the effect of spectral resolution in the speaker identification 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 (optimal number of MFSC). In fact, researchers do prefer using low spectral resolutions for many justifiable reasons, but we do not know what is the best resolution to adopt, especially in talker identification and we do not know what are the performances got with high spectral resolutions either. To find that optimal resolution, in microphonic and telephonic bandwidth,the authors have experimented several dimensions for the MFSC coefficients and several types of additive noises, at several SNR ratios. Results show the importance of the high spectral resolution in noisy environment and telephonic bandwidth, while the current research works have always favoured the low resolution of 24 coefficients in

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