Factored Translation between Brazilian Portuguese and English

Factored translation is an extension of the state-of-theart phrase-based statistical machine translation (PB-SMT). The main difference in factored translation approach is that a word is not only a token (its surface form) but a vector composed of different information such as lemma, part-of-speech or morphologic/syntactic tags. In this paper we present some experiments carried out to train and test factored translation models on Brazilian Portuguese and English texts. Using part-of-speech and morphological information, the factored models showed better results than the baseline (a PB-SMT), but the same gain in performance was not reached when flat syntactic tags were considered.