Conference paper

DEHAK Najim, KENNY Patrick, DEHAK Reda, GLEMBEK Ondřej, DUMOUCHEL Pierre, BURGET Lukáš, HUBEIKA Valiantsina and CASTALDO Fabio. Support vector machines and joint factor analysis for speaker verification. In: Proc. ICASSP 2009. Taiwan: IEEE Signal Processing Society, 2009, pp. 1-4. ISBN 978-1-4244-2354-5.
Publication language:english
Original title:Support vector machines and joint factor analysis for speaker verification
Title (cs):Support vector machines a joint factor analysis pro verifikaci mluvčího
Proceedings:Proc. ICASSP 2009
Conference:International Conference on Acoustics, Speech, and Signal Processing
Place:Taiwan, TW
Publisher:IEEE Signal Processing Society
Joint Factor Analysis, Support Vector Machine, Speaker factors space, Within Class Covariance Normalization
The paper is on support vector machines and joint factor analysis. Several variants of joint factor analysis are tested.
This article presents several techniques to combine between Support vector machines (SVM) and Joint Factor Analysis (JFA) model for speaker verification. In this combination, the SVMs are applied in different sources of information produced by the JFA. These informations are the Gaussian Mixture Model supervectors and speakers and Common factors. We found that the use of JFA factors gave the best results especially when within class covariance normalization method is applied in the speaker factors space in order to compensate for the channel effect. The new combination results are comparable to other classical JFA scoring techniques.
   author = {Najim Dehak and Patrick Kenny and Reda Dehak and
	Ond{\v{r}}ej Glembek and Pierre Dumouchel and
	Luk{\'{a}}{\v{s}} Burget and Valiantsina Hubeika
	and Fabio Castaldo},
   title = {Support vector machines and joint factor analysis
	for speaker verification},
   pages = {1--4},
   booktitle = {Proc. ICASSP 2009},
   year = {2009},
   location = {Taiwan, TW},
   publisher = {IEEE Signal Processing Society},
   ISBN = {978-1-4244-2354-5},
   language = {english},
   url = {}

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