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Holonic Multi-agent System Model for Fuzzy Automatic Speech / Speaker Recognition

  • J. J. Valencia-Jiménez
  • Antonio Fernández-Caballero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4953)

Abstract

An automatic speech / speaker recognition (ASSR) system has to adapt to possible changes of speaker and environment conditions, and act as close as possible to the way a human recognizes speeches / speakers. This kind of very complex system has to deal with speech signals, looking for the integration of different information sources; and this is precisely the reason to use fuzzy logic. The main objective of this paper is the description of a robust, intelligent and adaptive system, modeled as a multi-agent system (MAS), forming a recursive hierarchy of MAS denominated holonic MAS.

Keywords

Holony Multi-agent systems Fuzziness Speech recognition Speaker recognition 

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References

  1. 1.
    Beritelli, F., Casale, S., Cavallaro, A.: A robust voice activity detector for wireless communications using soft computing. IEEE Journal on Selected Areas in Communications, Special Issue on Signal Processing for Wireless Communications 16(9), 1818–1829 (1998)Google Scholar
  2. 2.
    Jang, J.S.R.: ANFIS: Adaptive-network-based fuzzy inference systems. IEEE Transactions on Systems, Man & Cybernetics 23, 665–685 (1993)CrossRefGoogle Scholar
  3. 3.
    Holland, J.: Adaptation in Natural and Artificial Systems. University of Michigan Press (1975)Google Scholar
  4. 4.
    Honma, N., Abe, K., Sato, M., Takeda, H.: Adaptive evolution of holon networks by an autonomous decentralized method. Applied Mathematics and Computation 91(1), 43–61 (1998)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Huang, B., Gou, H., Liu, W., Xie, M.: A framework for virtual enterprise control with the holonic manufacturing paradigm. Computers in Industry 49(3), 299–310 (2002)CrossRefGoogle Scholar
  6. 6.
    International Phonetic Association home page (2005), http://www.arts.gla.ac.uk/IPA/index.html
  7. 7.
    Jarvis, J., Rönnquist, R., McFarlane, D., Jain, L.: A team-based holonic approach to robotic assembly cell control. Journal of Network and Computer Applications 29(2–3), 160–176 (2005)Google Scholar
  8. 8.
    Koestler, A.: The Ghost in the Machine. Arkana Books (1971)Google Scholar
  9. 9.
    López, M.T., Fernández-Caballero, A., Fernández, M.A., Mira, J., Delgado, A.E.: Visual surveillance by dynamic visual attention method. Pattern Recognition 39(11), 2194–2211 (2006)CrossRefGoogle Scholar
  10. 10.
    Massaro, D.: Perceiving Talking Faces: From Speech Perception to a Behavioral Principle. The MIT Press, Cambridge (1998)Google Scholar
  11. 11.
    Myers, C.S., Rabiner, L.R.: A comparative study of several dynamic time-warping algorithms for connected word recognition. The Bell System Technical Journal 60(7), 1389–1409 (1981)Google Scholar
  12. 12.
    Padgham, L., Winikoff, M.: Developing Intelligent Agent Systems: A Practical Guide. Wiley, Chichester (2004)Google Scholar
  13. 13.
    Pavón, J., Gómez-Sanz, J., Fernández-Caballero, A., Valencia-Jiménez, J.J.: Development of intelligent multisensor surveillance systems with agents. Robotics and Autonomous Systems 55(12), 892–903 (2007)Google Scholar
  14. 14.
    Rabiner, L., Juang, B.H.: Fundamentals of Speech Recognition. Prentice-Hall, Englewood Cliffs (1993)Google Scholar
  15. 15.
    Russo, M.: FuGeNeSys: A genetic neural system for fuzzy modeling. IEEE Transactions on Fuzzy Systems 6(3), 373–388 (1998)CrossRefGoogle Scholar
  16. 16.
    Tsao, C., Gray, R.M.: An endpoint detector for LPC speech using residual error look-ahead for vector quantization applications. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 97–100 (1984)Google Scholar
  17. 17.
    Turing, A.M.: Computing Machinery and Intelligence. Mind 49, 433–460 (1950)CrossRefMathSciNetGoogle Scholar
  18. 18.
    Valencia-Jiménez, J.J., Fernández-Caballero, A.: Holonic multi-agent systems to integrate independent multi-sensor platforms in complex surveillance. In: Proceedings of the IEEE International Conference on Advanced Video and Signal based Surveillance, p. 49 (2006)Google Scholar
  19. 19.
    Zadeh, L.: From computing with numbers, to computing with words: A new paradigm. International Journal on Applied Mathematics 12(3), 307–324 (2002)zbMATHMathSciNetGoogle Scholar
  20. 20.
    Zadeh, L.: Fuzzy logic, neural networks and soft computing. Communications of the ACM 37(3), 77–84 (1994)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Zadeh, L.: Outline of a new approach to the analysis of complex systems and decisión processes. IEEE Transactions on Systems, Man and Cybernetics, 28–44 (1973)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • J. J. Valencia-Jiménez
    • 1
  • Antonio Fernández-Caballero
    • 1
  1. 1.Departmento de Sistemas InformáticosUniversidad de Castilla-La Mancha Escuela Politécnica Superior de AlbaceteAlbaceteSpain

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