Agenda-based user simulation for bootstrapping a POMDP dialogue system

  • Authors:
  • Jost Schatzmann;Blaise Thomson;Karl Weilhammer;Hui Ye;Steve Young

  • Affiliations:
  • Cambridge University, Cambridge, United Kingdom;Cambridge University, Cambridge, United Kingdom;Cambridge University, Cambridge, United Kingdom;Cambridge University, Cambridge, United Kingdom;Cambridge University, Cambridge, United Kingdom

  • Venue:
  • NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
  • Year:
  • 2007

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Abstract

This paper investigates the problem of bootstrapping a statistical dialogue manager without access to training data and proposes a new probabilistic agenda-based method for simulating user behaviour. In experiments with a statistical POMDP dialogue system, the simulator was realistic enough to successfully test the prototype system and train a dialogue policy. An extensive study with human subjects showed that the learned policy was highly competitive, with task completion rates above 90%.