Robust analysis and interpretation of spoken Chinese queries

Abstract

In spoken dialogue systems, a robust treatment is required for the input utterance due to the recognition errors and a large set of spontaneous speech phenomena. This paper describes a framework for robust analysis and interpretation of spoken language. This framework includes inherently robust mechanisms, i.e., robust semantic parsing and robust interpretation, and an additional component as well, i.e., recognition error correction. A preliminary evaluation demonstrates that a good robustness is achieved efficiently under this framework.