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Abstract

Applications of probabilistic grammatical inference are limited due to time and space consuming constraints. In statistical language modeling, for example, large corpora are now available and lead to managing automata with millions of states. We propose in this article a method for pruning automata (when restricted to tree based structures) which is not only efficient (sub-quadratic) but that allows to dramatically reduce the size of the automaton with a small impact on the underlying distribution. Results are evaluated on a language modeling task.

Keywords

Machine Translation Tree Automaton Pruning Method Quadratic Complexity Probabilistic Automaton 
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 2008

Authors and Affiliations

  • Franck Thollard
    • 1
  • Baptiste Jeudy
    • 1
  1. 1.Laboratoire Hubert Curien UMR CNR 5516Université de Lyon, Université Jean-MonnetFrance

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