STBU system for the NIST 2006 speaker recognition evaluation

被引：0

作者：

Matejka, P. ^{[1
]}

Burget, L. ^{[1
]}

Schwarz, P. ^{[1
]}

Glembek, O. ^{[1
]}

Karafiat, M. ^{[1
]}

Grezl, F. ^{[1
]}

Cernocky, J. ^{[1
]}

van Leeuwen, D. A. ^{[2
]}

Bruemmer, N. ^{[3
]}

Strasheim, A. ^{[4
]}

机构：

[1] Brno Univ Technol, Fac Informat Technol, Speech FIT, Brno, Czech Republic

[2] TNO Human Factors, Soesterberg, Netherlands

[3] Spescom Data Voice, Stellenbosch, South Africa

[4] Univ Stellenbosch, Dept Elect & Elect Engn, ZA-7600 Stellenbosch, South Africa

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL IV, PTS 1-3 | 2007年

关键词：

speaker recognition; GMM; SVM; eigen-channel; NAP;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

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.

引用

页码：221 / +

页数：2

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