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Discriminant NAP for SVM Speaker Recognition

Vogt, Robert J., Kajarekar, Sachin, & Sridharan, Sridha (2008) Discriminant NAP for SVM Speaker Recognition. In Odyssey 2008: The Speaker and Language Recognition Workshop, 21-24 January 2008, Stellenbosch, South Africa.

Abstract

Nuisance Attribute Projection (NAP) provides an effective method of removing the unwanted session variability in a Support Vector Machine (SVM) based speaker recognition system by removing the principal components of this variability. There is no guarantee with the methods proposed, however, that desired speaker variability is retained.

This paper investigates the possibility of training NAP discriminatively to remove session variability while maintaining desirable speaker variability through an approach which is a variation on Scatter Difference Analysis (SDA). Experiments on NIST SRE tasks with a GMM mean supervector SVM system demonstrate a modest improvement by using SDA for NAP training by adding some speaker scatter.

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369 since deposited on 25 Feb 2008
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ID Code: 12630
Item Type: Conference Paper
Additional Information: For more information, please refer to the conference’s website (see hypertext link) or contact the author.
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ISBN: 9780620403313
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2008 IEEE
Copyright Statement: 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.
Deposited On: 25 Feb 2008
Last Modified: 29 Feb 2012 23:48

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