Learning to balance grounding rationales for dialogue systems

Joshua Gordon, Rebecca Jane Passonneau, Susan L. Epstein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper reports on an experiment that investigates clarification subdialogues in intentionally noisy speech recognition. The architecture learns weights for mixtures of grounding strategies from examples provided by a human wizard embedded in the system. Results indicate that the architecture learns to eliminate misunderstandings reliably despite high word error rate.

Original languageEnglish (US)
Title of host publicationProceedings of the SIGDIAL 2011 Conference
Subtitle of host publication12th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Pages266-271
Number of pages6
StatePublished - Dec 1 2011
Event12th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2011 - Portland, OR, United States
Duration: Jun 17 2011Jun 18 2011

Publication series

NameProceedings of the SIGDIAL 2011 Conference: 12th Annual Meeting of the Special Interest Group on Discourse and Dialogue

Other

Other12th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2011
CountryUnited States
CityPortland, OR
Period6/17/116/18/11

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Modeling and Simulation

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  • Cite this

    Gordon, J., Passonneau, R. J., & Epstein, S. L. (2011). Learning to balance grounding rationales for dialogue systems. In Proceedings of the SIGDIAL 2011 Conference: 12th Annual Meeting of the Special Interest Group on Discourse and Dialogue (pp. 266-271). (Proceedings of the SIGDIAL 2011 Conference: 12th Annual Meeting of the Special Interest Group on Discourse and Dialogue).