A kernel trick for sequences applied to text-independent speaker verification systems

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摘要

This paper presents 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.

论文关键词:Support vector machines,Gaussian mixture models,Sequence kernel,Text-independent speaker verification

论文评审过程:Received 3 January 2006, Revised 23 November 2006, Accepted 3 January 2007, Available online 25 January 2007.

论文官网地址:https://doi.org/10.1016/j.patcog.2007.01.011