Deep linguistic processing for spoken dialogue systems

Abstract

We describe a framework for deep linguistic processing for natural language understanding in task-oriented spoken dialogue systems. The goal is to create domaingeneral processing techniques that can be shared across all domains and dialogue tasks, combined with domain-specific optimization based on an ontology mapping from the generic LF to the application ontology. This framework has been tested in six domains that involve tasks such as interactive planning, coordination operations, tutoring, and learning.