Conference paper

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.
Publication language:english
Original title:STBU system for the NIST 2006 speaker recognition evaluation
Title (cs):STBU systém pro NIST evaluaci rozpoznávání mluvčího 2006
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)
Place:Honolulu, US
Year:2007
ISBN:1-4244-0728-1
Publisher:IEEE Signal Processing Society
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2007/matejka_stbu_icassp_2007.pdf [PDF]
Keywords
Speaker recognition,GMM, SVM, eigenchannel, NAP.
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.
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.
BibTeX:
@INPROCEEDINGS{
   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 = {http://www.fit.vutbr.cz/research/view_pub.php?id=8250}
}

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