Scaling up POMDPs for Dialog Management: The ``Summary POMDP'' Method

  title={Scaling up POMDPs for Dialog Management: The ``Summary POMDP'' Method},
  author={J. D. Williams and Steve Young},
  journal={IEEE Workshop on Automatic Speech Recognition and Understanding, 2005.},
Partially observable Markov decision processes (POMDPs) have been shown to be a promising framework for dialog management in spoken dialog systems. However, to date, POMDPs have been limited to artificially small tasks. In this work, we present a novel method called a "summary POMDP" for scaling slot-filling POMDP-based dialog managers to cope with tasks of a realistic size. An example dialog problem incorporating a user model built from real dialog data is presented. A dialog manager is… CONTINUE READING
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A Framework for Unsupervised Learning of Dialogue Strategies

  • Olivier Pietquin
  • Ph D thesis, Faculty of Engineering,
  • 2004
1 Excerpt

A Framework for Wizard-of-Oz Experiments with a Simulated ASR-Channel

  • Matthew Stuttle, Jason D. Williams, Steve Young
  • International Conferences on Spoken Language…
  • 2004
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