Paper: A joint inference of deep case analysis and zero subject generation for Japanese-to-English statistical machine translation

ACL ID P14-2091
Title A joint inference of deep case analysis and zero subject generation for Japanese-to-English statistical machine translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We present a simple joint inference of deep case analysis and zero subject gener- ation for the pre-ordering in Japanese-to- English machine translation. The detec- tion of subjects and objects from Japanese sentences is more difficult than that from English, while it is the key process to gen- erate correct English word orders. In addi- tion, subjects are often omitted in Japanese when they are inferable from the context. We propose a new Japanese deep syntac- tic parser that consists of pointwise proba- bilistic models and a global inference with linguistic constraints. We applied our new deep parser to pre-ordering in Japanese-to- English SMT system and show substantial improvements in automatic evaluations.