A Robust System for Natural Spoken Dialogue

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.

• Publication year

  1996

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  1996-06-18

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/981863.981872arXiv cmp-lg/9606023
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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