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Local methods for on-demand out-of-vocabulary word retrieval

Abstract : Most of the Web-based methods for lexicon augmenting consist in capturing global semantic features of the targeted domain in order to collect relevant documents from the Web. We suggest that the local context of the out-of-vocabulary (OOV) words contains relevant information on the OOV words. With this information, we propose to use the Web to build locally-augmented lexicons which are used in a final local decoding pass. First, an automatic web based OOV word detection method is proposed. Then, we demonstrate the relevance of the Web for the OOV word retrieval. Different methods are proposed to retrieve the hypothesis words. We finally retrieve about 26% of the OOV words with a lexicon increase of less than 1000 words using the reference context.
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https://hal.archives-ouvertes.fr/hal-01319850
Contributor : Bibliothèque Universitaire Déposants Hal-Avignon <>
Submitted on : Monday, May 23, 2016 - 10:17:13 AM
Last modification on : Thursday, February 11, 2021 - 8:20:08 AM

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  • HAL Id : hal-01319850, version 1

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Stanislas Oger, Georges Linarès, Frédéric Béchet. Local methods for on-demand out-of-vocabulary word retrieval. LREC, May 2008, Marrakech, Morocco. ⟨hal-01319850⟩

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