Paper: Soft Dependency Matching for Hierarchical Phrase-based Machine Translation

ACL ID C14-1210
Title Soft Dependency Matching for Hierarchical Phrase-based Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

This paper proposes a soft dependency matching model for hierarchical phrase-based (HPB) machine translation. When a HPB rule is extracted, we enrich it with dependency knowledge automatically learnt from the training data. The dependency knowledge not only encodes the dependency relations between the components inside the rule, but also contains the dependency relations between the rule and its con- text. When a rule is applied to translate a sentence, the dependency knowledge is used to compute the syntactic structural consistency of the rule against the dependency tree of the sentence. We characterize the structure consistency by three features and integrate them into the standard SMT log-linear model to guide the translation process. Our method is evaluated on multiple Chinese-to...