Layered Charts for Speech Translation

We are going to present an architecture for natural language processing systems especially designed for spontaneous speech. We introduce the notion of a layered chart for information separation and information hiding. Complex distributed systems can be built using this approach which do not rely on a central data structure or control model. We describe a typed feature formalism with appropriateness suitable for such systems by providing a compact and relocatable storage schema for feature structures. We set out an architecture for spontaneous speech translation that relies on partial parsing to minimize complex operations at an early syntactic stage, but rather carries out utterance integration after building up small scale syntactic objects. We adopt the notion of a variable depth of analysis by providing a module specialized to the translation of idioms and show how an global scoring schema for sub-paths in graphs can be used to block further operation on idioms already accounted for.