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A further investigation on speech features for speaker characterization

In this article, we investigate on alternative speech features for speaker characterization. We study Line Spectrum Pairs features, Time-Frequency Principal Components and Discriminant Components of the Spectrum. These alternative features are tested and compared on a task of speaker veriﬁcation. This task consists in verifying a claimed identity from a speech segment. Systems are evaluated on a subset of the evaluation data of the NIST 1999 speaker recognition campaign. The new speech features are also compared to the classical cepstral coefﬁcients, which remain, in our experiments, the best performing features.