Paper: Better Synchronous Binarization for Machine Translation

ACL ID D09-1038
Title Better Synchronous Binarization for Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

Binarization of Synchronous Context Free Grammars (SCFG) is essential for achieving polynomial time complexity of decoding for SCFG parsing based machine translation sys- tems. In this paper, we first investigate the excess edge competition issue caused by a left- heavy binary SCFG derived with the method of Zhang et al. (2006). Then we propose a new binarization method to mitigate the problem by exploring other alternative equivalent bi- nary SCFGs. We present an algorithm that ite- ratively improves the resulting binary SCFG, and empirically show that our method can im- prove a string-to-tree statistical machine trans- lations system based on the synchronous bina- rization method in Zhang et al. (2006) on the NIST machine translation evaluation tasks.