融合格框架的基于语块的依存树到串日汉统计机器翻译模型

该文提出了一种融合格框架的日汉基于语块的依存树到串统计机器翻译模型。其基本思想是从日语依存分析树获取格框架,在翻译模型的规则抽取及解码中,以日语格框架作为约束条件,指导依存树的句法结构重排,调整日语和汉语的句法结构差异,实现格框架与日汉依存树到串模型的融合。实验结果表明,该文提出的方法可有效改善日汉统计机器翻译的句法结构调序和词汇翻译,同时,还可有效提高日汉统计机器翻译的译文质量。

Chunk-based Dependency-to-String Model Using Case Frame for Japanese-Chinese Statistical Machine Translation

This paper proposes a method to integrate case frame into Japanese to Chinese chunk-based dependency-to-string model. Firstly, case frames are acquired from Japanese chunk-based dependency analysis results. Secondly, case frames are used to constrain the rule extraction and the decoding in chunk-based dependency-to-string model. Experimental results show that the proposed method performs well on long structural reordering and lexical translation, and achieves better performance than hierarchical phrase-based model and word-based dependency-to-string model on Japanese to Chinese test sets.