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.
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.
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|Item Type:||Conference Paper|
|Additional Information:||For more information, please refer to the publisher's website (see hypertext link) or contact the author.|
|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
Past > Schools > School of Engineering Systems
|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. http://www.springer.de/comp/lncs/ Lecture Notes in Computer Science|
|Deposited On:||25 Feb 2008 00:00|
|Last Modified:||29 Feb 2012 13:40|
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