DocumentCode
3309797
Title
Maximizing Distance between GMMs for Speaker Verification
Author
Kim, Min-Seok ; Yang, Il-Ho ; Yu, Ha-Jin
Author_Institution
Sch. of Comput. Sci., Univ. of Seoul, Seoul
Volume
6
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
175
Lastpage
178
Abstract
In this paper, we propose a feature transformation method to maximize the distances between the Gaussian mixture models for speaker verification. The feature transformation matrix is optimized by using particle swarm optimization. We evaluate the transformation using YOHO speech data, and the transformation is applied to some speakers who give poor performance. As the result, the overall equal error rate is reduced to 1.71% from 1.97% of the baseline.
Keywords
Gaussian processes; matrix algebra; particle swarm optimisation; speaker recognition; GMM; Gaussian mixture models; YOHO speech data; feature transformation matrix; feature transformation method; particle swarm optimization; speaker verification; Computer science; Covariance matrix; Density functional theory; Error analysis; Feature extraction; Humans; Optimization methods; Particle swarm optimization; Speaker recognition; Speech analysis; GMM; PSO; Speaker Verification;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.820
Filename
4667824
Link To Document