Paper: Reordering Constraints For Phrase-Based Statistical Machine Translation

ACL ID C04-1030
Title Reordering Constraints For Phrase-Based Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

In statistical machine translation, the gen- eration of a translation hypothesis is com- putationally expensive. If arbitrary re- orderings are permitted, the search prob- lem is NP-hard. On the other hand, if we restrict the possible reorderings in an appropriate way, we obtain a polynomial-time search algorithm. We in- vestigate different reordering constraints for phrase-based statistical machine trans- lation, namely the IBM constraints and the ITG constraints. We present effi- cient dynamic programming algorithms for both constraints. We evaluate the con- straints with respect to translation quality on two Japanese–English tasks. We show that the reordering constraints improve translation quality compared to an un- constrained search that permits arbitrary phrase reorderings. The IT...