Abstract
This paper presents a cluster-based feature transformation technique for telephone-based speaker verification when labels of the handset types are not available during the training phase. The technique combines a cluster selector with cluster-dependent feature transformations to reduce the acoustic mismatches among different handsets. Specifically, a GMM-based cluster selector is trained to identify the cluster that best represents the handset used by a claimant. Handset distorted features are then transformed by cluster-specific feature transformation to remove the acoustic distortion before being presented to the clean speaker models. Experimental results show that cluster-dependent feature transformation with number of clusters larger than the actual number of handsets can achieve a performance level very close to that achievable by the handset-based transformation approaches.
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This work was supported by The Hong Kong Polytechnic University Grant No. A442 and HKSAR RGC Grant No. PolyU5129/01E. S.Y. Kung was also a Distinguished Chair Professor of The Hong Kong Polytechnic University.
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References
M.W. Mak and S.Y. Kung, “Combining stochastic feautre transformation and handset identification for telephone-based speaker verification,” in Proc. ICASSP’2002, 2002, pp. I701–I704.
A. Sankar and C.H. Lee, “A maximum-likelihood approach to stochastic matching for robust speech recognition,” IEEE Trans. on Speech and Audio Processing, vol. 4, no. 3, pp. 190–202, 1996.
C. L. Tsang, M.W. Mak, and S. Y. Kung, “Divergence-based out-of-class rejection for telephone handset identification,” in Proc. ICSLP’02, 2002, pp. 2329–2332.
A.P. Dempster, N. M. Laird, and D.B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” J. of Royal Statistical Soc., Ser. B., vol. 39, no. 1, pp. 1–38, 1977.
D.A. Reynolds, “HTIMIT and LLHDB: speech corpora for the study of handset transducer effects,” in ICASSP’97, 1997, vol. 2, pp. 1535–1538.
Eric W.M. Yu, M. W. Mak, and S.Y. Kung, “Speaker verification from coded telephone speech using stochastic feature transformation and handset identification,” in Pacific-Rim Conference on Multimedia 2002, 2002, pp. 598–606.
S.B. Davis and P. Mermelstein, “Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences,” IEEE Trans. on ASSP, vol. 28, no. 4, pp. 357–366, August 1980.
H.C. Wang C. S. Liu and C.H. Lee, “Speaker verification using normalized loglikelihood score,” IEEE Trans on Speech and Audio Processing, vol. 4, no. 1, pp. 56–60, 1996.
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© 2003 Springer-Verlag Berlin Heidelberg
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Tsang, CL., Mak, MW., Kung, SY. (2003). Cluster-Dependent Feature Transformation for Telephone-Based Speaker Verification. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_11
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DOI: https://doi.org/10.1007/3-540-44887-X_11
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