First Result on Arabic Neural Machine Translation

Understand

Neural machine translation has become a major alternative to widely used phrase-based statistical machine translation.

• We notice however that much of research on neural machine translation has focused on European languages despite its language agnostic nature.
• In this paper, we apply neural machine translation to the task of Arabic translation (Ar<->En) and compare it against a standard phrase-based translation system.
• We run extensive comparison using various configurations in preprocessing Arabic script and show that the phrase-based and neural translation systems perform comparably to each other and that proper preprocessing of Arabic script has a similar effect on both of the systems.