Paper: Local Phrase Reordering Models For Statistical Machine Translation

ACL ID H05-1021
Title Local Phrase Reordering Models For Statistical Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

We describe stochastic models of local phrase movement that can be incorpo- rated into a Statistical Machine Transla- tion (SMT) system. These models pro- vide properly formulated, non-deficient, probability distributions over reordered phrase sequences. They are imple- mented by Weighted Finite State Trans- ducers. We describe EM-style parameter re-estimation procedures based on phrase alignment under the complete translation model incorporating reordering. Our ex- periments show that the reordering model yields substantial improvements in trans- lation performance on Arabic-to-English and Chinese-to-English MT tasks. We also show that the procedure scales as the bitext size is increased.