Dependency-based Reordering Model for Constituent Pairs in Hierarchical SMT

We propose a novel dependency-based reordering 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 structure of the source sentence to capture the mediumand long-distance reorderings between these pairs of constituents. We describe our reordering model in detail and then apply it to a language pair in which the languages involved follow different word order patterns, English (SVO) and Farsi (free word order being SOV the most frequent pattern). Our model outperforms a baseline (standard hierarchical SMT) by 0.78 BLEU points absolute, statistically significant at p = 0.01.

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