• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

Efficient Speaker Identification based on Robust VQ-PCA


Lee Ki-Yong, Journal of Internet Computing and Services, Vol. 5, No. 3, pp. 57-62, Jun. 2004
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Keywords: Speaker identification, GMM, M-estimation, VQ, PCA

Abstract

In this paper, an efficient speaker identification based on robust vector quantizationprincipal component analysis (VQ-PCA) is proposed to solve the problems from outliers and high dimensionality of training feature vectors in speaker identification, Firstly, the proposed method partitions the data space into several disjoint regions by roust VQ based on M-estimation. Secondly, the robust PCA is obtained from the covariance matrix in each region. Finally, our method obtains the Gaussian Mixture model (GMM) for speaker from the transformed feature vectors with reduced dimension by the robust PCA in each region, Compared to the conventional GMM with diagonal covariance matrix, under the same performance, the proposed method gives faster results with less storage and, moreover, shows robust performance to outliers.


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Cite this article
[APA Style]
Lee Ki-Yong (2004). Efficient Speaker Identification based on Robust VQ-PCA. Journal of Internet Computing and Services, 5(3), 57-62.

[IEEE Style]
L. Ki-Yong, "Efficient Speaker Identification based on Robust VQ-PCA," Journal of Internet Computing and Services, vol. 5, no. 3, pp. 57-62, 2004.

[ACM Style]
Lee Ki-Yong. 2004. Efficient Speaker Identification based on Robust VQ-PCA. Journal of Internet Computing and Services, 5, 3, (2004), 57-62.