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A Deep Source-Context Feature for Lexical Selection in Statistical Machine Translation

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A Deep Source-Context Feature for Lexical Selection in Statistical Machine Translation

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Gupta, PA.; Costa-Jussa, MR.; Rosso, P.; Banchs, R. (2016). A Deep Source-Context Feature for Lexical Selection in Statistical Machine Translation. Pattern Recognition Letters. 75:24-29. doi:10.1016/j.patrec.2016.02.014

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Título: A Deep Source-Context Feature for Lexical Selection in Statistical Machine Translation
Autor:
Entidad UPV: Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Fecha difusión:
Resumen:
This paper presents a methodology to address lexical disambiguation in a standard phrase-based statistical machine translation system. Similarity among source contexts is used to select appropriate translation units. The ...[+]
Palabras clave: Natural language processing , Neural nets and related approaches , Semantics
Derechos de uso: Embargado
Fuente:
Pattern Recognition Letters. (issn: 0167-8655 )
DOI: 10.1016/j.patrec.2016.02.014
Editorial:
Elsevier
Versión del editor: http://dx.doi.org/10.1016/j.patrec.2016.02.014
Descripción: this is the author’s version of a work that was accepted for publication in Pattern Recognition Letters . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters 75 (2016) 24–29. DOI 10.1016/j.patrec.2016.02.014.
Agradecimientos:
The work of the first author has been supported by FPI UPV pre-doctoral grant (num. registro - 3505). The work of the second author has been supported by Spanish Ministerio de Economia y Competitividad, contract TEC2015-69266-P ...[+]
Tipo: Artículo

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