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Harnessing Models of Users’ Goals to Mediate Clarification Dialog in Spoken Language Systems

  • Eric Horvitz
  • Tim Paek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)

Abstract

Speaker-independent speech recognition systems are being used with increasing frequency for command and control applications. To date, users of such systems must contend with their fragility to subtle changes in language usage and environmental acoustics. We describe work on coupling speech recognition systems with temporal probabilistic user models that provide inferences about the intentions associated with utterances. The methods can be employed to enhance the robustness of speech recognition by endowing systems with an ability to reason about the costs and benefits of action in a setting and to make decisions about the best action to take given uncertainty about the meaning behind acoustic signals. The methods have been implemented in the form of a dialog clarification module that can be integrated with legacy spoken language systems. We describe representation and inference procedures and present details on the operation of an implemented spoken command and control development environment called DeepListener.

Keywords

Dialog systems clarification dialog spoken command and control speech recognition conversational systems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Eric Horvitz
    • 1
  • Tim Paek
    • 1
  1. 1.One Microsoft Way Microsoft ResearchRedmond

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