This article describes techniques of vocal forgery able to affect automatic speaker recognition system in a forensic context. Vocal forgery covers two main aspects: voice transformation and voice conversion. Concerning voice transformation, this article proposes an automatic analysis of four specific disguised voices in order to detect the forgery and, for voice conversion, different ways to au...

iv Chapter

This paper describes the fusion technology for speaker recognition. First,these feature sets are extracted form the same speech signal, and then the correlations between the feature sets are analyzed, only the uncorrelation feature sets can be combined. The single feature set and combined feature set are compared. Experiments show that the performance of combined feature set is better than the ...

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A method of decision making which leads to the formation of a gain vector by utilizing a design set of patterns from only the class to be recognized is proposed. Some comparisons of this method with the adaline technique have been made and the method has been applied to the practical problem of speaker verification.

In this paper, we study how discriminative and Maximum Likelihood (ML) techniques should be combined in order to maximize the recognition accuracy of a speaker-independent Automatic Speech Recognition (ASR) system that includes speaker adaptation. We compare two training approaches for speaker-independent case and examine how well they perform together with four different speaker adaptation sch...

This chapter presents some of the main contributions in several topics of speaker recognition since 1978. Representative books and surveys on speaker recognition published during this period are listed. Theoretical models for automatic speaker recognition are contrasted with practical design methodology. Research contributions to measure process, feature extraction, and classification are selec...