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A novel speaker identification algorithm using classifiers fusion

  • King Fahd University of Petroleum and Minerals

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

1 Scopus citations

Abstract

In this paper, a novel speaker identification technique using the Dempster-Shafer evidence theory is discussed. The objective is to fuse the complementary information present from different classifiers into a single decision. Here, we use a decreasing function of the distance (of the classifiers) as the belief function. We show that a combined classifier based on the Dempster-Shafer theory outperforms the individual LPCC and MFCC classifiers when used individually.

Original languageEnglish
Title of host publication10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
Pages145-148
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010 - Kuala Lumpur, Malaysia
Duration: 10 May 201013 May 2010

Publication series

Name10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010

Conference

Conference10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
Country/TerritoryMalaysia
CityKuala Lumpur
Period10/05/1013/05/10

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