Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37653
Title: A new two-stage scoring normalization approach to speaker verification
Authors: Mak, MW 
Zhang, WD
He, MX
Keywords: Decision theory
Formal verification
Speaker recognition
Issue Date: 2001
Source: Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2001, 02 May 2001-04 May 2001, Hong Kong, p. 107-110 How to cite?
Abstract: In speaker verification, the cohort and world models have been separately used for scoring normalization. The authors embed the two models in elliptical basis function networks and propose a two-stage decision procedure for improving verification performance. The procedure begins with normalization of an utterance by a world model. If the difference between the resulting score and a world threshold is sufficiently large, the claimant is accepted or rejected immediately. Otherwise, the score will be normalized by a cohort model, and the resulting score will be compared with a cohort threshold to make a final accept/reject decision. Experimental evaluations based on the YOHO corpus suggest that the two-stage method achieves a lower error rate as compared to the case where only one background model is used
URI: http://hdl.handle.net/10397/37653
ISBN: 962-85766-2-3
DOI: 10.1109/ISIMP.2001.925343
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