Exploiting syntactic relationships in a phrase-based decoder: an exploration

Phrase-based decoding is conceptually simple and straightforward to implement, at the cost of drastically oversimplified reordering models. Syntactically aware models make it possible to capture linguistically relevant relationships in order to improve word order, but they can be more complex to implement and optimise. In this paper, we explore a new middle ground between phrase-based and syntactically informed statistical MT, in the form of a model that supplements conventional, non-hierarchical phrase-based techniques with linguistically informed reordering based on syntactic dependency trees. The key idea is to exploit linguisticallyinformed hierchical structures only for those dependencies that cannot be captured within a single flat phrase. For very local dependencies we leverage the success of conventional phrase-based approaches, which provide a sequence of target-language words appropriately ordered and ready-made with any agreement morphology. Working with dependency trees ...

• Type: Journal
• Year: 2010
• Where: MT
• Authors: Tim Hunter, Philip Resnik
• Keywords: Conventional Phrase-based Approaches, Dependency Trees, MT 2010, Non-hierarchical Phrase-based Techniques