A robust system for natural spoken dialogue

  • Authors:
  • James F. Allen;Bradford W. Miller;Eric K. Ringger;Teresa Sikorski

  • Affiliations:
  • University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY

  • Venue:
  • ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
  • Year:
  • 1996

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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.