A Kernel Trick For Sequences Applied to Text-Independent Speaker Verification Systems

This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also proposed. The new system is compared to state-of-the-art GMM and other SVM based systems found in the literature on the Banca and Polyvar databases. The new system outperforms, most of the time, the other systems, statistically significantly. Finally, the new proposed framework clarifies previous SVM based systems and suggests interesting future research directions.


Published in:
Pattern Recognition
Year:
2007
Note:
IDIAP-RR 05-77
Laboratories:




 Record created 2010-02-11, last modified 2018-09-13

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