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EBMT by tree-phrasing

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Machine Translation

Abstract

This article presents an attempt to build a repository storing associations between simple syntactic dependency treelets in a source language and their corresponding phrases in a target language. We assess the usefulness of this resource in two different settings. First, we show that it improves upon a standard subsentential translation memory. Second, we observe improvements in translation quality when a standard statistical phrase-based translation engine is augmented with the ability to exploit such a repository.

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Authors and Affiliations

  1. RALI-DIRO, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Qué, Canada, H3C 3J7

    Philippe Langlais & Fabrizio Gotti

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  1. Philippe Langlais
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  2. Fabrizio Gotti
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Correspondence to Philippe Langlais.

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Langlais, P., Gotti, F. EBMT by tree-phrasing. Machine Translation 20, 1–23 (2006). https://doi.org/10.1007/s10590-006-9017-3

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