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	基于图的统计机器翻译词汇化调序模型(英文)
	苏劲松 ; 刘洋 ; 刘群 ; 董槐林 ; SU Jinsong ; LIU Yang ; LIU Qun ; DONG Huailin
	2016-03-30 ; 2016-03-30
关键词	natural language processing statistical machine translation lexicalized reordering model reordering graph TP391.2
其他题名	Graph-based Lexicalized Reordering Models for Statistical Machine Translation
中文摘要	Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.; Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.
语种	英语 ; 英语
内容类型	期刊论文
源URL	[http://ir.lib.tsinghua.edu.cn/ir/item.do?handle=123456789/141953]
专题	清华大学
推荐引用方式 GB/T 7714	苏劲松,刘洋,刘群,等. 基于图的统计机器翻译词汇化调序模型(英文)[J],2016, 2016.
APA	苏劲松.,刘洋.,刘群.,董槐林.,SU Jinsong.,...&DONG Huailin.(2016).基于图的统计机器翻译词汇化调序模型(英文)..
MLA	苏劲松,et al."基于图的统计机器翻译词汇化调序模型(英文)".(2016).

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