Title :
ICSI´S 2005 speaker recognition system
Author :
Mirghafori, Nikki ; Hatch, Andrew O. ; Stafford, Steven ; Boakye, Kofi ; Gillick, Daniel ; Peskin, Barbara
Author_Institution :
Int. Comput. Sci. Inst., Berkeley, CA
Abstract :
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
Keywords :
Gaussian processes; cepstral analysis; hidden Markov models; speaker recognition; support vector machines; Gaussian mixture model; HMM system; SVM; cepstral GMM System; lattice phone n-gram system; sequential nonparametric system; speaker recognition evaluation; speaker recognition system; Cepstral analysis; Computer science; Hidden Markov models; Lattices; NIST; Performance evaluation; Power system modeling; Speaker recognition; Testing; Training data;
Conference_Titel :
Automatic Speech Recognition and Understanding, 2005 IEEE Workshop on
Conference_Location :
San Juan
Print_ISBN :
0-7803-9478-X
Electronic_ISBN :
0-7803-9479-8
DOI :
10.1109/ASRU.2005.1566512
