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Differential Evolution Applied to a Multimodal Information Theoretic Optimization Problem

  • Patricia Besson
  • Jean-Marc Vesin
  • Vlad Popovici
  • Murat Kunt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3907)

Abstract

This paper discusses the problems raised by the optimization of a mutual information-based objective function, in the context of a multimodal speaker detection. As no approximation is used, this function is highly nonlinear and plagued by numerous local minima. Three different optimization methods are compared. The Differential Evolution algorithm is deemed to be the best for the problem at hand and, consequently, is used to perform the speaker detection.

Keywords

Mutual Information Differential Evolution Differential Evolution Algorithm Mouth Region Audio Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Butz, T., Thiran, J.P.: From error probability to information theoretic (multi-modal) signal processing. Signal Process 85, 875–902 (2005)MATHCrossRefGoogle Scholar
  2. 2.
    Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C, 2nd edn. Cambridge University Press, Cambridge (1992)MATHGoogle Scholar
  3. 3.
    Schroeter, P., Vesin, J.M., Langenberger, T., Meuli, R.: Robust parameter estimation of intensity distributions for brain magnetic resonance images. IEEE Trans. Med. Imaging 17(2), 172–186 (1998)CrossRefGoogle Scholar
  4. 4.
    Storn, R., Price, K.: Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. J. Global Optim. 11, 341–359 (1997)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Besson, P., Popovici, V., Vesin, J., Kunt, M.: Extraction of audio features specific to speech using information theory and differential evolution. EPFL-ITS Tech. Rep. 2005-018, EPFL, Lausanne, Switzerland (2005)Google Scholar
  6. 6.
    Besson, P., Kunt, M., Butz, T., Thiran, J.P.: A multimodal approach to extract optimized audio features for speaker detection. In: Proc. EUSIPCO (2005)Google Scholar
  7. 7.
    Leung, Y.W., Wang, Y.: An orthogonal genetic algorithm with quantization for global numerical optimization. IEEE Trans. Evo. Comp. 5(1), 41–53 (2001)CrossRefGoogle Scholar
  8. 8.
    Price, K.V.: 6: An Introduction to Differential Evolution. In: New Ideas in Optimization, pp. 79–108. McGraw-Hill, New York (1999)Google Scholar
  9. 9.
    Storn, R.: Differential evolution homepage [online] (Available), http://www.icsi.berkeley.edu/storn/code.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Patricia Besson
    • 1
  • Jean-Marc Vesin
    • 1
  • Vlad Popovici
    • 1
  • Murat Kunt
    • 1
  1. 1.Signal Processing Institute, EPFLLausanneSwitzerland

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