Improved Statistical Machine Translation Using MultiWord Expressions

Identifying and translating a MultiWord Expression (MWE) in a text represents an issue for numerous applications in Natural Language Processing (NLP) as MWEs appear in all text genres and pose significant problems for every kind of NLP tasks. In this paper, we describe a hybrid approach for extracting contiguous MWEs and their translations in a FrenchEnglish parallel corpus. We evaluate both the alignment and the translation quality. Next, we implement a method that integrates these units to Moses, the state of the art Machine Translation (MT) system. Conducted experiments show that MWEs improve translation performance.

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