Information based speaker verification
2000 (English)Conference paper (Refereed)Text
We discuss the conceptual and computational frameworks of information theory for decision making in speaker verification. The proposed approach departs from other conventional scoring models for speaker verification as the first approach takes into account the quantity of `surprise' or information content. We compare the new approach with a widely used log-likelihood normalization method for speaker verification. Experimental results on a commercial speech corpus validates the theoretical foundation of the proposed method. Furthermore, we introduce the unique entropic measure of uncertainty in the verification scoring
Place, publisher, year, edition, pages
2000. Vol. 3, 278-281 p.
Information Systems, Social aspects
IdentifiersURN: urn:nbn:se:liu:diva-125049DOI: 10.1109/ICPR.2000.903539ISBN: 0-7695-0750-6OAI: oai:DiVA.org:liu-125049DiVA: diva2:902711
15th International Conference on Pattern Recognition, 2000..03 Sep 2000-07 Barcelona