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.
Cite
CITATION STYLE
Nederhof, M. J. (2000). Practical experiments with regular approximation of context-free languages. Computational Linguistics, 26(1), 17–44. https://doi.org/10.1162/089120100561610
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