Toward open-set text-independent speaker identification in tactical communications

Matt B. Wolf, Won Kyung Park, Jae C. Oh, Misty K. Blowers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We present the design and implementation of an open-set textindependent speaker identification system using genetic Learning Classifier Systems (LCS). We examine the use of this system in a real-number problem domain, where there is strong interest in its application to tactical communications. We investigate different encoding methods for representing real-number knowledge and study the efficacy of each method for speaker identification. We also identify several difficulties in solving the speaker identification problems with LCS and introduce new approaches to resolve the difficulties. Experimental results show that our system successfully learns 200 voice features at accuracies of 90 % to 100 % and 15,000 features to more than 80% for the closed-set problem, which is considered a strong result in the speaker identification community. The open-set capability is also comparable to existing numeric-based methods.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA 2007
Pages7-14
Number of pages8
DOIs
StatePublished - Sep 25 2007
Event2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA 2007 - Honolulu, HI, United States
Duration: Apr 1 2007Apr 5 2007

Publication series

NameProceedings of the 2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA 2007

Other

Other2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA 2007
CountryUnited States
CityHonolulu, HI
Period4/1/074/5/07

Keywords

  • Classifier systems
  • Genetic algorithms
  • Language and speech
  • Machine learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computational Mathematics
  • Theoretical Computer Science

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