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Large-scale Word Alignment Using Soft Dependency Cohesion Constraints
Zhiguo,Wang; Chengqing, Zong
2013
发表期刊Transactions of Association for Computational Linguistics(TACL)
期号1页码:291-300
摘要Dependency cohesion refers to the observation that phrases dominated by disjoint dependency subtrees in the source language generally do not overlap in the target language. It has been verified to be a useful constraint for word alignment. However, previous work either treats this as a hard constraint or uses it as a feature in discriminative models, which is ineffective for large-scale tasks. In this paper, we take dependency cohesion as a soft constraint, and integrate it into a generative model for large-scale word alignment experiments. We also propose an approximate EM algorithm and a Gibbs sampling algorithm to estimate model parameters in an unsupervised manner. Experiments on large-scale Chinese-English translation tasks demonstrate that our model achieves improvements in both alignment quality and translation quality.
关键词Large-scale Word Alignment
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12363
专题模式识别国家重点实验室_自然语言处理
通讯作者Zhiguo,Wang
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Zhiguo,Wang,Chengqing, Zong. Large-scale Word Alignment Using Soft Dependency Cohesion Constraints[J]. Transactions of Association for Computational Linguistics(TACL),2013(1):291-300.
APA Zhiguo,Wang,&Chengqing, Zong.(2013).Large-scale Word Alignment Using Soft Dependency Cohesion Constraints.Transactions of Association for Computational Linguistics(TACL)(1),291-300.
MLA Zhiguo,Wang,et al."Large-scale Word Alignment Using Soft Dependency Cohesion Constraints".Transactions of Association for Computational Linguistics(TACL) .1(2013):291-300.
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