Syntactic phrase reordering for English-to-Arabic statistical machine translation

Syntactic Reordering of the source language to better match the phrase structure of the target language has been shown to improve the performance of phrase-based Statistical Machine Translation. This paper applies syntactic reordering to English-to-Arabic translation. It introduces reordering rules, and motivates them linguistically. It also studies the effect of combining reordering with Arabic morphological segmentation, a preprocessing technique that has been shown to improve Arabic-English and English-Arabic translation. We report on results in the news text domain, the UN text domain and in the spoken travel domain.