Publication Details

STBU system for the NIST 2006 speaker recognition evaluation

MATĚJKA Pavel, BURGET Lukáš, SCHWARZ Petr, GLEMBEK Ondřej, KARAFIÁT Martin, GRÉZL František, ČERNOCKÝ Jan, VAN Leeuwen David, BRÜMMER Niko and STRASHEIM Albert. STBU system for the NIST 2006 speaker recognition evaluation. In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007). Honolulu: IEEE Signal Processing Society, 2007, pp. 221-224. ISBN 1-4244-0728-1.
Type
conference paper
Language
english
Authors
Matějka Pavel, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Schwarz Petr, Ing., Ph.D. (DCGM FIT BUT)
Glembek Ondřej, Ing., Ph.D. (DCGM FIT BUT)
Karafiát Martin, Ing., Ph.D. (DCGM FIT BUT)
Grézl František, Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, doc. Dr. Ing. (DCGM FIT BUT)
van Leeuwen David (TNO TPD)
Brümmer Niko (Agnitio)
Strasheim Albert (USB)
URL
Keywords

Speaker recognition,GMM, SVM, eigenchannel, NAP.

Abstract

This paper describes STBU 2006 speaker recognition system, which performed well in the NIST 2006 speaker recognition evaluation. STBU is consortium of 4 partners: Spescom DataVoice (South Africa), TNO (Netherlands), BUT (Czech Republic) and University of Stellenbosch (South Africa). The primary system is a combination of three main kinds of systems: (1) GMM, with short-time MFCC or PLP features, (2) GMM-SVM, using GMM mean supervectors as input and (3) MLLR-SVM, using MLLR speaker adaptation coefficients derived from English LVCSR system. In this paper, we describe these sub-systems and present results for each system alone and in combination on the NIST Speaker Recognition Evaluation (SRE) 2006 development and evaluation data sets.

Annotation

This paper describes STBU 2006 speaker recognition system, which performed well in the NIST 2006 speaker recognition evaluation. STBU is consortium of 4 partners: Spescom DataVoice (South Africa), TNO (Netherlands), BUT (Czech Republic) and University of Stellenbosch (South Africa). The primary system is a combination of three main kinds of systems: (1) GMM, with short-time MFCC or PLP features, (2) GMM-SVM, using GMM mean supervectors as input and (3) MLLR-SVM, using MLLR speaker adaptation coefficients derived from English LVCSR system. In this paper, we describe these sub-systems and present results for each system alone and in combination on the NIST Speaker Recognition Evaluation (SRE) 2006 development and evaluation data sets.

Published
2007
Pages
221-224
Proceedings
Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)
Conference
32nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, US
ISBN
1-4244-0728-1
Publisher
IEEE Signal Processing Society
Place
Honolulu, US
BibTeX
@INPROCEEDINGS{FITPUB8250,
   author = "Pavel Mat\v{e}jka and Luk\'{a}\v{s} Burget and Petr Schwarz and Ond\v{r}ej Glembek and Martin Karafi\'{a}t and Franti\v{s}ek Gr\'{e}zl and Jan \v{C}ernock\'{y} and David Leeuwen van and Niko Br{\"{u}}mmer and Albert Strasheim",
   title = "STBU system for the NIST 2006 speaker recognition evaluation",
   pages = "221--224",
   booktitle = "Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)",
   year = 2007,
   location = "Honolulu, US",
   publisher = "IEEE Signal Processing Society",
   ISBN = "1-4244-0728-1",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/8250"
}
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