TAILIEUCHUNG - Báo cáo khoa học: "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. | A Comparative Study of Target Dependency Structures for Statistical Machine Translation Xianchao Wu Katsuhito Sudoh Kevin Duh Hajime Tsukada Masaaki Nagata NTT Communication Science Laboratories NTT Corporation 2-4 Hikaridai Seika-cho Soraku-gun Kyoto 619-0237 Japan wuxianchao@ kevinduh@ @ Abstract 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. 1 Introduction Target language side dependency structures have been successfully used in statistical machine translation SMT by Shen et al. 2008 and achieved state-of-the-art results as reported in the NIST 2008 Open MT Evaluation workshop and the NTCIR-9 Chinese-to-English patent translation task Goto et al. 2011 Ma and Matsoukas 2011 . A primary advantage of dependency representations is that they have a natural mechanism for representing discontinuous constructions which arise due to longdistance dependencies or in languages where grammatical relations are often signaled by morphology instead of word order McDonald and Nivre 2011 . It is known that dependency-style structures can be transformed from a number of linguistic struc Now at Baidu Inc. t Now at Nara Institute of Science Technology NAIST 100 tures. For example using the constituent-to-dependency conversion approach proposed by Johansson and Nugues 2007 we can easily yield dependency trees from PCFG style trees. A semantic .

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