Fuzzy normalisation methods for speaker verification

Dat Tran, Michael Wagner

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

4 Citations (Scopus)

Abstract

This paper proposes normalisation methods based on fuzzy set theory for speaker verification. A claimed speaker's score used to accept or reject this speaker is viewed as a fuzzy membership function. We propose two scores: the fuzzy entropy and fuzzy C-means membership functions. Moreover, a likelihood transformation is considered to obtain a general approach and, based on this, five more fuzzy scores are proposed. Finally, a noise clustering method is applied to the current and proposed methods, reducing the equal error rate in all cases. Experiments performed on the ANDOSL and YOHO speech corpora show better results for all proposed methods.

Original languageEnglish
Title of host publication6th International Conference on Spoken Language Processing, ICSLP 2000
Place of PublicationUnited States
PublisherInternational Speech Communication Association
Pages1-4
Number of pages4
ISBN (Electronic)9787801501141
Publication statusPublished - 2000
Event6th International Conference on Spoken Language Processing, ICSLP 2000 - Beijing, China
Duration: 16 Oct 200020 Oct 2000

Publication series

Name6th International Conference on Spoken Language Processing, ICSLP 2000

Conference

Conference6th International Conference on Spoken Language Processing, ICSLP 2000
CountryChina
CityBeijing
Period16/10/0020/10/00

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