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2010

A Joint Rule Selection Model for Hierarchical Phrase-Based Translation

10 years 2 months ago
A Joint Rule Selection Model for Hierarchical Phrase-Based Translation
In hierarchical phrase-based SMT systems, statistical models are integrated to guide the hierarchical rule selection for better translation performance. Previous work mainly focused on the selection of either the source side of a hierarchical rule or the target side of a hierarchical rule rather than considering both of them simultaneously. This paper presents a joint model to predict the selection of hierarchical rules. The proposed model is estimated based on four sub-models where the rich context knowledge from both source and target sides is leveraged. Our method can be easily incorporated into the practical SMT systems with the log-linear model framework. The experimental results show that our method can yield significant improvements in performance.
Lei Cui, Dongdong Zhang, Mu Li, Ming Zhou, Tiejun
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Lei Cui, Dongdong Zhang, Mu Li, Ming Zhou, Tiejun Zhao
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