Pivot probability induction for statistical machine translation with topic similarity

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	Pivot probability induction for statistical machine translation with topic similarity
	Huang, Yanz ; Shi, Xiaodon ; Su, Jinsong ; Chen, Yido ; Huang, Guimin ; Shi XD(史晓东)
刊名	http://dx.doi.org/10.12733/jcis8450
	2013-10-15
关键词	Natural language processing systems Semantics
英文摘要	Previous works employ the pivot language approach to conduct statistical machine translation when encountering with limited amount of bilingual corpus. Conventional solutions based upon phrase-table combination overlook the semantic discrepancy between the source-pivot corpus and pivot-target corpus and consequently lead to probability estimation inaccuracy for the induced translation rules. In this paper, the latent topic structure of the document-level training data is learned automatically and each phrase translation rule is assigned to a topic distribution. Furthermore, the phrase probability induction is carried out on the basis of the topic similarity, allowing the translation system to consider the semantic relatedness among different rules. Using BLEU as a metric of translation accuracy, we find out our system is capable of achieving a absolute improvement in in-domain test compared with the baseline system. ? 2013 Binary Information Press.
语种	英语
出版者	Binary Information Press
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/92637]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Huang, Yanz,Shi, Xiaodon,Su, Jinsong,et al. Pivot probability induction for statistical machine translation with topic similarity[J]. http://dx.doi.org/10.12733/jcis8450,2013.
APA	Huang, Yanz,Shi, Xiaodon,Su, Jinsong,Chen, Yido,Huang, Guimin,&史晓东.(2013).Pivot probability induction for statistical machine translation with topic similarity.http://dx.doi.org/10.12733/jcis8450.
MLA	Huang, Yanz,et al."Pivot probability induction for statistical machine translation with topic similarity".http://dx.doi.org/10.12733/jcis8450 (2013).