Automatic Detection of Translated Text and its Impact on Machine Translation

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TypeArticle
Proceedings titleProceedings. MT Summit XII, The twelfth Machine Translation Summit International Association for Machine Translation hosted by the Association for Machine Translation in the Americas
ConferenceMT Summit XII, The twelfth Machine Translation Summit International Association for Machine Translation hosted by the Association for Machine Translation in the Americas, Ottawa, Ontario, August 26-30, 2009
AbstractWe investigate the possibility of automatically detecting whether a piece of text is an original or a translation. On a large parallel English-French corpus where reference information is available, we find that this is possible with around 90% accuracy. We further study the implication this has on Machine Translation performance. After separating our corpus according to translation direction, we train direction-specific phrase-based MT systems and show that they yield improved translation performance. This suggests that taking directionality into account when training SMT systems may have a significant effect on output quality.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Information Technology
Peer reviewedYes
NPARC number16335045
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Record identifier335e44df-2f0a-47b4-be0f-f59e3e00f1a4
Record created2010-11-05
Record modified2016-05-09
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