Practical experiments with regular approximation of context-free languages

  • Authors:
  • Mark-Jan Nederhof

  • Affiliations:
  • German Research Center for Artificial Intelligence

  • Venue:
  • Computational Linguistics - Special issue on finite-state methods in NLP
  • Year:
  • 2000

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Abstract

Several methods are discussed that construct a finite automaton given a context-free grammar, including both methods that lead to subsets and those that lead to supersets of the original context-free language. Some of these methods of regular approximation are new, and some others are presented here in a more refined form with respect to existing literature. Practical experiments with the different methods of regular approximation are performed for spoken-language input: hypotheses from a speech recognizer are filtered through a finite automaton.