A Comparative Study of Target Dependency Structures for Statistical Machine Translation

This paper presents a comparative study of target dependency structures yielded by several state-of-the-art linguistic parsers. Our approach is to measure the impact of these nonisomorphic dependency structures to be used for string-to-dependency translation. Besides using traditional dependency parsers, we also use the dependency structures transformed from PCFG trees and predicate-argument structures (PASs) which are generated by an HPSG parser and a CCG parser. The experiments on Chinese-to-English translation show that the HPSG parser’s PASs achieved the best dependency and translation accuracies.

• Type: Journal
• Year: 2012
• Where: ACL
• Authors: Xianchao Wu, Katsuhito Sudoh, Kevin Duh, Hajime Tsukada, Masaaki Nagata
• Keywords: ACL 2012, Chinese To English Translation, Computational Linguistics, Dependency Structures, Target