Context-aware discriminative phrase selection for statistical machine translation
Jesus Vicente Gimenez, Lluı́s Màrquez · 2007
In this work we revise the application of discriminative learning to the problem of phrase selection in Statistical Machine Translation. Inspired by common techniques used in Word Sense Disambiguation, we train classifiers based on local context to predict possible phrase translations. Our work extends that of Vickrey et al. (2005) in two main aspects. First, we move from word translation to phrase translation. Second, we move from the 'blank-filling' task to the 'full translation' task. We report results on a set of highly frequent source phrases, obtaining a significant improvement, specially with respect to adequacy, according to a rigorous process of manual evaluation.