Speaker Identification Using Glottal-Source Waveforms and Support-Vector-Machine Modelling

David Vandyke, Michael Wagner, Girija Chetty, Roland Goecke

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

Speaker identification experiments are performed with novel features representative of the glottal source waveform. These are derived from closed-phase analysis and inverse filtering. Source waveforms are segmented into two consecutive periods and normalised in prosody, forming so called source-frame feature vectors. Support-vector-machines are used to construct speaker discriminative hyperplanes and identification rates are reported. Groups of male speakers of size 5 to 20 are examined from the YOHO corpus and 65% correct identification rates are achieved on a per source-frame basis. Finally the source-frames phonetic independence is confirmed with the TI 46-Word corpus.
Original languageEnglish
Title of host publicationProceedings of the 14th Australasian International Conference on Speech Science and Technology
EditorsFelicity Cox, Katherine Demuth, Susan Lin, Kelly Miles, Sallyanne Palethrope, Jason Shaw, Ivan Yuen
Place of PublicationSydney, Australia
PublisherAustralasian Speech Science and Technology Association (ASSTA)
Pages49-52
Number of pages4
Publication statusPublished - 2012
Event14th Australasian International Conference on Speech Science and Technology - Sydney, Sydney, Australia
Duration: 3 Dec 20126 Dec 2012

Publication series

NameASSTA 2013
PublisherAustralasian Speech Science and Technology Association
ISSN (Print)1039-0227

Conference

Conference14th Australasian International Conference on Speech Science and Technology
CountryAustralia
CitySydney
Period3/12/126/12/12

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