Dependency-based Reordering Model for Constituent Pairs in Hierarchical SMT

We propose a novel dependency-based re-ordering model for hierarchical SMT that predicts the translation order of two types of pairs of constituents of the source tree: head-dependent and dependent-dependent. Our model uses the dependency struc-ture of the source sentence to capture the medium- and long-distance reorder-ings between these pairs of constituents. We describe our reordering model in de-tail and then apply it to a language pair in which the languages involved follow dif-ferent word order patterns, English (SVO) and Farsi (free word order being SOV the most frequent pattern). Our model out-performs a baseline (standard hierarchical SMT) by 0.78 BLEU points absolute, sta-tistically significant at p = 0.01.