Conference paper

CUMANI Sandro, BRÜMMER Niko, BURGET Lukáš and LAFACE Pietro. Fast Discriminative Speaker Verification in the I-Vector Space. In: Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011. Praha: IEEE Signal Processing Society, 2011, pp. 4852-4855. ISBN 978-1-4577-0537-3.
Publication language:english
Original title:Fast Discriminative Speaker Verification in the I-Vector Space
Title (cs):Rychlé diskriminativní ověřování mluvčího v i-vektorovém prostoru
Pages:4852-4855
Proceedings:Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Conference:International Conference on Acoustics, Speech and Signal Processing 2011
Place:Praha, CZ
Year:2011
ISBN:978-1-4577-0537-3
Publisher:IEEE Signal Processing Society
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2011/cumani_icassp2011_4852.pdf [PDF]
Keywords
Discriminative Training,Two-covariance Kernel, Support Vector Machines, i-vectors
Annotation
A fast discriminative training approach for speaker verification based on i-vectors has been presented. On NIST telephone evaluation data, the resulting models perform better, without the need for normalization techniques, than the generative ones, even compared with heavy-tailed models.
Abstract
This work presents a new approach to discriminative speaker verification. Rather than estimating speaker models, or a model that discriminates between a speaker class and the class of all the other speakers, we directly solve the problem of classifying pairs of utterances as belonging to the same speaker or not. The paper illustrates the development of a suitable Support Vector Machine kernel from a state-of-the-art generative formulation, and proposes an efficient approach to train discriminative models. The results of the experiments performed on the tel-tel extended core condition of the NIST 2010 Speaker Recognition Evaluation are competitive or better, in terms of normalized Decision Cost Function and Equal Error Rate, compared to the more expensive generative models.
BibTeX:
@INPROCEEDINGS{
   author = {Sandro Cumani and Niko Brümmer and Lukáš Burget and Pietro
	Laface},
   title = {Fast Discriminative Speaker Verification in the I-Vector
	Space},
   pages = {4852--4855},
   booktitle = {Proceedings of the 2011 IEEE International Conference on
	Acoustics, Speech, and Signal Processing, ICASSP 2011},
   year = {2011},
   location = {Praha, CZ},
   publisher = {IEEE Signal Processing Society},
   ISBN = {978-1-4577-0537-3},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=9654}
}

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