Forest Driven Dependency Analysis Enhanced by Japanese Clause Structure Estimation

For applications of the natural language processing, such as spoken translation, it is the most important characteristic to accept various inputs. We analyze a speech input as a sequence of speech fragment and achieve high acceptability. But it is difficult to determine whether each fragment/unit should be interpreted separately or not. This sort of problem is shared by several applications. We regard a clause and dependency structures as one of the clue to solve this type of problem. Because, even in a spoken language domain, a clause represents a syntactic unit and a dependency represents a semantic unit. In this paper, we describe the dependency analysis method on the syntax forest structure enhanced by Japanese clause structure estimation. It also contributes to improve on translation in manual evaluation from 77.8% up to 78.8%.