Handling phrase reorderings for machine translation

We propose a distance phrase reordering model (DPR) for statistical machine trans-lation (SMT), where the aim is to cap-ture phrase reorderings using a structure learning framework. On both the reorder-ing classification and a Chinese-to-English translation task, we show improved perfor-mance over a baseline SMT system.