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Speaker verification using sequence discriminant support vector machines

Wan, V. and Renals, S. (2005) Speaker verification using sequence discriminant support vector machines. IEEE Transactions on Speech and Audio Processing, 13 (2). pp. 203-210. ISSN 1063-6676


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This paper presents a text-independent speaker verification system using support vector machines (SVMs) with score-space kernels. Score-space kernels generalize Fisher kernels and are based on underlying generative models such as Gaussian mixture models (GMMs). This approach provides direct discrimination between whole sequences, in contrast with the frame-level approaches at the heart of most current systems. The resultant SVMs have a very high dimensionality since it is related to the number of parameters in the underlying generative model. To address problems that arise in the resultant optimization we introduce a technique called spherical normalization that preconditions the Hessian matrix. We have performed speaker verification experiments using the PolyVar database. The SVM system presented here reduces the relative error rates by 34% compared to a GMM likelihood ratio system.

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Fisher kernel, score-space kernel, speaker verification, support vector machine
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Repository Officer
Date Deposited: 02 Dec 2005
Last Modified: 13 Jun 2014 10:17
Published Version: http://dx.doi.org/10.1109/TSA.2004.841042
Status: Published
Refereed: Yes
Identification Number: 10.1109/TSA.2004.841042
URI: http://eprints.whiterose.ac.uk/id/eprint/813

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