A Comparison of Session Variability Compensation Techniques for SVM-Based Speaker Recognition
McLaren, Mitchell L., Vogt, Robert J., Baker, Brendan J., & Sridharan, Sridha (2007) A Comparison of Session Variability Compensation Techniques for SVM-Based Speaker Recognition. In Interspeech 2007, August 27-31, Antwerp, Belgium.
This paper compares two of the leading techniques for session variability compensation in the context of GMM mean supervector SVM classifiers for speaker recognition: inter-session variability modelling and nuisance attribute projection. The former is incorporated in the GMM model training while the latter is employed as a modified SVM kernel. Results on both the NIST 2005 and 2006 corpora demonstrate the effectiveness of both techniques for reducing the effects of session variation. Further, system- and score-level fusion experiments show that the combination of the two methods provides improved performance.
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|Item Type:||Conference Paper|
|Additional Information:||For more information, please refer to the conference’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 > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Institutes > Information Security Institute
|Copyright Owner:||Copyright 2007 (please consult author)|
|Deposited On:||25 Feb 2008|
|Last Modified:||29 Feb 2012 23:40|
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