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Immunocomputing for Speaker Recognition

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Advances in Machine Learning II

Part of the book series: Studies in Computational Intelligence ((SCI,volume 263))

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Abstract

Based on mathematical models of immunocomputing, this chapter proposes an approach to speaker recognition by intelligent signal processing. The approach includes both low-level feature extraction and high-level ("intelligent") pattern recognition. The key model is the formal immune network (FIN) including apoptosis (programmed cell death) and immunization both controlled by cytokines (messenger proteins). Such FIN can be formed from audio signals using discrete tree transform (DTT), singular value decomposition (SVD), and the proposed index of inseparability in comparison with the Renyi entropy. Application is demonstrated on the task of recognizing nine male speakers by their utterances of two Japanese vowels. The obtained results suggest that the proposed approach outperforms state of the art approaches of computational intelligence.

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Author information

Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation, Russian Academy of Sciences, 14-line 39, St. Petersburg, 199178, Russia

    Alexander O. Tarakanov

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  1. Alexander O. Tarakanov
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Editors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warsaw, Poland

    Jacek Koronacki  & Sławomir T. Wierzchoń  & 

  2. Woodward Hall 430C, University of North Carolina, 9201 University City Blvd., N.C. 28223, Charlotte, USA

    Zbigniew W. RaÅ›

  3. Systems Research Institute, Polish Academy of Sciences, ul.Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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Tarakanov, A.O. (2010). Immunocomputing for Speaker Recognition. In: Koronacki, J., Raś, Z.W., Wierzchoń, S.T., Kacprzyk, J. (eds) Advances in Machine Learning II. Studies in Computational Intelligence, vol 263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05179-1_24

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  • DOI: https://doi.org/10.1007/978-3-642-05179-1_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05178-4

  • Online ISBN: 978-3-642-05179-1

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