ICSI'S 2005 speaker recognition system

This paper describes ICSI's 2005 speaker recognition system, which was one of the top performing systems in the NIST 2005 speaker recognition evaluation. The system is a combination of four sub-systems: 1) a keyword conditional HMM system, 2) an SVM-based lattice phone n-gram system, 3) a seque...

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Bibliographic Details
Published inIEEE Workshop on Automatic Speech Recognition and Understanding, 2005 pp. 23 - 28
Main Authors Mirghafori, N., Hatch, A.O., Stafford, S., Boakye, K., Gillick, D., Peskin, B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Cepstral analysis
Computer science
Hidden Markov models
Lattices
NIST
Performance evaluation
Power system modeling
Speaker recognition
Testing
Training data
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Summary:This paper describes ICSI's 2005 speaker recognition system, which was one of the top performing systems in the NIST 2005 speaker recognition evaluation. The system is a combination of four sub-systems: 1) a keyword conditional HMM system, 2) an SVM-based lattice phone n-gram system, 3) a sequential nonparametric system, and 4) a traditional cepstral GMM System, developed by SRI. The first three systems are designed to take advantage of higher-level and long-term information. We observe that their performance is significantly improved when there is more training data. In this paper, we describe these sub-systems and present results for each system alone and in combination on the speaker recognition evaluation (SRE) 2005 development and evaluation data sets
ISBN:078039478X
9780780394780
DOI:10.1109/ASRU.2005.1566512