On-line incremental adaptation for speaker verification using maximum likelihood estimates of CDHMM parameters
نویسندگان
چکیده
This papers investigates two approaches to on-line incremental adaptation of CDHMM parameters. First the popular MAP approach is examined, highlighting di culties in automatically setting the adaptation rate. To overcome these problems we introduce a new approach based on the multi-observation estimation equations of the forward-backward algorithm called a cumulative likelihood estimate (CLE). Experimental results using these two approaches are compared with and without the use of a speech model for enrolment on isolated word speaker models. In both enrolment procedures, the CLE approach can achieve approximately an EER of 1% for six adaptation sequences using a single digit test token.
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