Features for phoneme independent speaker identification

Jianglin Wang, An Ji, Michael T. Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper describes a unique cross-phoneme speaker identification experiment, using deliberately mismatched phoneme sets for training and testing. The underlying goal is to identify features that represent broad individually unique characteristics rather than those that represent phonetic differences, as are more typical of modern speaker identification and verification systems. A wide range of features are proposed and evaluated within this context using a Gaussian Mixture Model framework. The results show that log-area ratio has better phonetic independence than MFCCs, that residual phase carries substantial speaker information, and identifies several other features that also have usefulness for speaker identification independent of phonetic content.

Original languageEnglish
Title of host publicationICALIP 2012 - 2012 International Conference on Audio, Language and Image Processing, Proceedings
Pages1141-1145
Number of pages5
DOIs
StatePublished - 2012
Event2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012 - Shanghai, China
Duration: Jul 16 2012Jul 18 2012

Publication series

NameICALIP 2012 - 2012 International Conference on Audio, Language and Image Processing, Proceedings

Conference

Conference2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012
Country/TerritoryChina
CityShanghai
Period7/16/127/18/12

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Vision and Pattern Recognition

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