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Evolution of speech recognizer agents by artificial life

Halavati, R ; Sharif University of Technology | 2005

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  1. Type of Document: Article
  2. Publisher: 2005
  3. Abstract:
  4. Artificial Life can be used as an agent training approach in large state spaces. This paper presents an artificial life method to increase the training speed of some speech recognizer agents which where previously trained by genetic algorithms. Using this approach, vertical training (genetic mutations and selection) is combined with horizontal training (individual learning through reinforcement learning) and results in a much faster evolution than simple genetic algorithm. The approach is tested and a comparison with GA cases on a standard speech data base is presented. COPYRIGHT © ENFORMATIKA
  5. Keywords:
  6. Database systems ; Fuzzy sets ; Genetic algorithms ; Personnel training ; Agent training approach ; Fuzzy modeling ; Speech recognizer agents ; Speech recognition
  7. Source: Wec 05: Fourth World Enformatika Conference, Istanbul, 24 June 2005 through 26 June 2005 ; Volume 6 , 2005 , Pages 237-240 ; 9759845857 (ISBN)
  8. URL: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.193.4566&rep=rep1&type=pdf