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Constructing Song Syntax by Automata Induction

  • Kazutoshi Sasahara
  • Yasuki Kakishita
  • Tetsuro Nishino
  • Miki Takahasi
  • Kazuo Okanoya
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4201)

Abstract

We propose a new methodology for ethology in terms of automata induction. Recent studies on Bengalese finch reported unique features of its songs. As opposed to most other songbirds, the songs of the Bengalese finch are neither monotonous nor random; they can be represented by a finite automaton, which we call song syntax [3]. Juvenile finches learn songs from their fathers during a critical period. The song learning has a similarity to the grammatical inference from positive samples, which is known as Angluin’s algorithm [1]. This is an induction algorithm for inferring certain subclasses of regular languages, which are known as k-reversible languages, from positive samples, where k = 0,1,2,.... A regular language is k-reversible under the following condition: whenever two prefixes whose last k words match have a tail in common, then these prefixes have all tails in common. For each k, Angluin’s algorithm provides a finite automaton that accepts the smallest k-reversible language, including the given finite positive sample within polynomial time.

Keywords

Regular Language Finite Automaton Courtship Song Word Match Song Learning 
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.
    Angluin, D.: Inference of Reversible Languages. Journal of the Association for Computing Machinery 29(3), 741–765 (1982)zbMATHMathSciNetGoogle Scholar
  2. 2.
    Berwick, R.C., Pilato, S.F.: Learning Syntax by Automata Induction. Machine Learning 2(1), 9–38 (1987)Google Scholar
  3. 3.
    Okanoya, K.: Song Syntax in Bengalese Finches: Proximate and Ultimate Analyses. Advances in the Study of Behavior 34, 297–346 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kazutoshi Sasahara
    • 1
  • Yasuki Kakishita
    • 2
  • Tetsuro Nishino
    • 2
  • Miki Takahasi
    • 1
  • Kazuo Okanoya
    • 1
  1. 1.Laboratory for Biolinguistics, RIKEN Brain Science Institute (BSI)SaitamaJapan
  2. 2.Department of Information and Communication Engineering, Graduate School of Electro-CommunicationsThe University of Electro-CommunicationsChofu-shi, TokyoJapan

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