Keywords

spoken dialogue systems, speech interpretation, recognition errors

Abstract

This paper describes a system that leads us to believe in the feasibility of constructing natural spoken dialogue systems in task-oriented domains. It specifically addresses the issue of robust interpretation of speech in the presence of recognition errors. Robustness is achieved by a combination of statistical error post-correction, syntactically- and semantically-driven robust parsing, and extensive use of the dialogue context. We present an evaluation of the system using time-to-completion and the quality of the final solution that suggests that most native speakers of English can use the system successfully with virtually no training.

Original Publication Citation

James F. Allen, Bradford W. Miller, Eric K. Ringger, and Teresa Sikorski. June 1996. "A Robust System for Natural Spoken Dialogue." Proceedings of the 34th Annual Meeting of the Association for Computational Linguistics (ACL'96). Santa Cruz, CA.