Paper: Synchronous Binarization For Machine Translation

ACL ID N06-1033
Title Synchronous Binarization For Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2006
Authors

Systems based on synchronous grammars and tree transducers promise to improve the quality of statistical machine transla- tion output, but are often very computa- tionally intensive. The complexity is ex- ponential in the size of individual gram- mar rules due to arbitrary re-orderings be- tween the two languages, and rules ex- tracted from parallel corpora can be quite large. We devise a linear-time algorithm for factoring syntactic re-orderings by bi- narizing synchronous rules when possible and show that the resulting rule set signif- icantly improves the speed and accuracy of a state-of-the-art syntax-based machine translation system.