Paper: Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures

ACL ID C14-1176
Title Synchronous Constituent Context Model for Inducing Bilingual Synchronous Structures
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

Traditional Statistical Machine Translation (SMT) systems heuristically extract synchronous structures from word alignments, while synchronous grammar induction provides better so- lutions that can discard heuristic method and directly obtain statistically sound bilingual syn- chronous structures. This paper proposes Synchronous Constituent Context Model (SCCM) for synchronous grammar induction. The SCCM is different to all previous synchronous grammar induction systems in that the SCCM does not use the Context Free Grammars to model the bilin- gual parallel corpus, but models bilingual constituents and contexts directly. The experiments show that valuable synchronous structures can be found by the SCCM, and the end-to-end ma- chine translation experiment shows that the SCCM improves the q...