SVM speaker verification using session variability modelling and GMM supervectors

McLaren, Mitchell L., Vogt, Robert J., & Sridharan, Sridha (2007) SVM speaker verification using session variability modelling and GMM supervectors. In Lee, S.-W. & Li, S.Z. (Eds.) Proceedings of : 2nd International Conference, ICB 2007 : Advances in Biometrics, August 27-29, 2007, Seoul, Korea.

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This paper demonstrates that modelling session variability during GMM training can improve the performance of a GMM supervector SVM speaker verification system. Recently, a method of modelling session variability in GMM-UBM systems has led to significant improvements when the training and testing conditions are subject to session effects. In this work, session variability modelling is applied during the extraction of GMM supervectors prior to SVM speaker model training and classification. Experiments performed on the NIST 2005 corpus show major improvements over the baseline GMM supervector SVM system.

Impact and interest:

6 citations in Scopus
2 citations in Web of Science®
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232 since deposited on 25 Feb 2008
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ID Code: 7559
Item Type: Conference Paper
Refereed: Yes
Additional Information: For more information, please refer to the publisher's website (see hypertext link) or contact the author.
DOI: 10.1007/978-3-540-74549-5_112
ISBN: 9783540745488
ISSN: 1611-3349
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 2007 Springer
Copyright Statement: This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. Lecture Notes in Computer Science
Deposited On: 25 Feb 2008 00:00
Last Modified: 03 Jul 2017 03:01

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