Identifying bilingual Multi-Word Expressions for Statistical Machine Translation

被引：0
|
作者：
Bouamor, Dhouha [1 ,2 ,3 ]
Semmar, Nasredine [1 ]
Zweigenbaum, Pierre [2 ,3 ]
机构：
[1] CEA, LIST, Vis & Content Engn Lab, F-91191 Gif Sur Yvette, France
[2] CNRS, LIMSI, F-91403 Orsay, France
[3] Univ Paris 11, Orsay, France
来源：
LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2012年
关键词：
bilingual Multi-Word Expression; Vector Space Model; Statistical Machine Translation;
D O I：
暂无
中图分类号：
H0 [语言学];
学科分类号：
030303 ; 0501 ; 050102 ;
摘要：
MultiWord Expressions (MWEs) repesent a key issue for numerous applications in Natural Language Processing (NLP) especially for Machine Translation (MT). In this paper, we describe a strategy for detecting translation pairs of MWEs in a French-English parallel corpus. In addition we introduce three methods aiming to integrate extracted bilingual MWES in MOSES, a phrase based Statistical Machine Translation (SMT) system. We experimentally show that these textual units can improve translation quality.
引用
收藏
页码：674 / 679
页数：6
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