Using Contextual Knowledge to Improve Parallel Spoken Language Understanding

Abstract

This paper presents a parallel approach for utilizing contextual knowledge to improve spoken language understanding. The method emphasizes a hierarchically-structured knowledge base and a memory-based parsing technique. Within this paradigm, several levels of knowledge sources including contextual knowledge arc efficiently combined. An ambiguity resolution scheme utilizing the preceding discourse context and the situational context was implemented on a parallel computer using a marker-passing scheme. The experiments on the parallel computer for an Air Traffic Control (ATC) domain show an 86% sentence recognition accuracy with about 6% improvement compared with the system not utilizing the contextual knowledge.