A problem in data variability on speaker identification system using hidden markov model

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Abstract

The paper addresses a problem on speaker identification system using Hidden Markov Model (HMM) caused by the training data selected far from its distribution centre. Four scenarios for unguided data have been conducted to partition the data into training data and testing data. The data were recorded from ten speakers. Each speaker uttered 80 times with the same physical (health) condition. The data collected then pre-processed using Mel-Frequence Cepstrum Coefficients (MFCC) feature extraction method. The four scenarios are based on the distance of each speech to its distribution centre, which is computed using Self Organizing Map (SOM) algorithm. HMM with many number of states (from 3 up to 7) showed that speaker with multi-modals distribution will drop the system accuracy up to 9% from its highest recognition rate, i.e. 100%.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
Pages29-33
Number of pages5
Publication statusPublished - 1 Dec 2008
EventIASTED International Conference on Artificial Intelligence and Applications, AIA 2008 - Innsbruck, Austria
Duration: 13 Feb 200815 Feb 2008

Publication series

NameProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008

Conference

ConferenceIASTED International Conference on Artificial Intelligence and Applications, AIA 2008
CountryAustria
CityInnsbruck
Period13/02/0815/02/08

Keywords

  • Hidden markov model
  • Mel-frequence cepstrum coefficients
  • Self organizing map

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  • Cite this

    Buono, A., & Putro, B. K. (2008). A problem in data variability on speaker identification system using hidden markov model. In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 (pp. 29-33). (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).