Learning phonetic rules in a speech recognition system

  • Zoltán Alexin
  • János Csirik
  • Tibor Gyimóthy
  • Mark Jelasity
  • László Tóth
Part II Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1297)


Current speech recognition systems can be categorized into two broad classes; the knowledge-based approach and the stochastic one. In this paper we present a rule-based method for the recognition of Hungarian vowels. A spectrogram model was used as a front-end module and some acoustic features were extracted (e.g. locations, intensities and shapes of local maxima) from spectrograms by using a genetic algorithm method. On the basis of these features we developed a rule set for the recognition of isolated Hungarian vowels. These rules represented by Prolog clauses were refined by the IMPUT Inductive Logic Programming method.


Speech Recognition Speech Signal Acoustic Feature Inductive Logic Programming Speech Recognition System 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Zoltán Alexin
    • 1
  • János Csirik
    • 2
  • Tibor Gyimóthy
    • 3
  • Mark Jelasity
    • 3
  • László Tóth
    • 3
  1. 1.Department of Applied InformaticsJózsef Attila UniversitySzegedHungary
  2. 2.Department of Computer ScienceJózsef Attila UniversitySzegedHungary
  3. 3.Research Group on Artificial IntelligenceHungarian Academy of SciencesSzegedHungary

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