Handling phrase reorderings for machine translation
Yizhao Ni, Craig Saunders, Sandor Szedmak, Mahesan Niranjan
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework. On both the reordering classification and a Chinese-to-English translation task, we show improved performance over a baseline SMT system.
ACL-IJCNLP 2009 (Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing), Suntec, Singapore, August 2-7, 2009