Grouping Multi-word Expressions According to Part-Of-Speech in Statistical Machine Translation

This paper studies a strategy for identifying and using multi-word expressions in Statistical Machine Translation. The performance of the proposed strategy for various types of multi-word expressions (like nouns or verbs) is evaluated in terms of alignment quality as well as translation accuracy. Evaluations are performed by using real-life data, namely the European Parliament corpus. Results from translation tasks from English-to-Spanish and from Spanish-to-English are presented and discussed.

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