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Discarding Impossible Events from Statistical Language Models

Armelle Brun 1 David Langlois 1 Kamel Smaïli 1 Jean-Paul Haton 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper describes a method for detectingvimpossible bigrams using a vocabulary of V elements. The idea is to discard all the ungrammatical events to expect an improvement of the language model. We extract the impossible bigrams by using automatic rules. The biclass associations which are ungrammatical are detected and all the corresponding bigrams are analyzed and set as possible or impossible events, we also decided to manage for each of the retrieved rule an exception list.
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https://hal.inria.fr/inria-00099040
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Submitted on : Tuesday, September 26, 2006 - 8:47:37 AM
Last modification on : Monday, September 24, 2018 - 9:04:03 AM
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  • HAL Id : inria-00099040, version 1

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Armelle Brun, David Langlois, Kamel Smaïli, Jean-Paul Haton. Discarding Impossible Events from Statistical Language Models. International Conference on Spoken Language Processing, Oct 2000, Pékin, China, 4 p. ⟨inria-00099040⟩

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