Cluster-dependent feature transformation for telephone-based speaker verification

Authors:
Chi-Leung Tsang;Man-Wai Mak;Sun-Yuan Kung
Affiliations:
Center for Multimedia Signal Processing, Dept. of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China;Center for Multimedia Signal Processing, Dept. of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China;Dept. of Electrical Engineering, Princeton University
Venue:
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Year:
2003

Citing 2
Cited 0

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PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
HTIMIT and LLHDB: Speech Corpora for the Study of Handset Transducer Effects

ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2

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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.