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Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification

McLaren, Mitchell L., Baker, Brendan J., Vogt, Robert J., & Sridharan, Sridha (2010) Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification. In Proceedings of 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2010), IEEE, Sheraton Dallas Hotel, Dallas, Texas, pp. 4434-4437.

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Abstract

This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.

Impact and interest:

2 citations in Scopus
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2 citations in Web of Science®

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60 since deposited on 19 May 2010
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ID Code: 32297
Item Type: Conference Paper
Additional URLs:
Keywords: Speaker Verification, Support Vector Machines
ISBN: 9781424442966
ISSN: 1520-6149
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2010 IEEE
Copyright Statement: ©2010 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.
Deposited On: 20 May 2010 08:56
Last Modified: 01 Mar 2012 00:16

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