Journal
COMPUTER SPEECH AND LANGUAGE
Volume 24, Issue 2, Pages 150-174Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.csl.2009.04.001
Keywords
Statistical dialogue systems; POMDP; Hidden Information State model
Categories
Funding
- UK EPSRC [EP/F013930/1]
- EU FP7 [216594]
- EPSRC [EP/F013930/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/F013930/1] Funding Source: researchfish
Ask authors/readers for more resources
This paper explains how Partially Observable Markov Decision Processes (POMDPs) can provide a principled mathematical framework for modelling the inherent uncertainty in spoken dialogue systems. It briefly summarises the basic mathematics and explains why exact optimisation is intractable. It then describes in some detail a form of approximation called the Hidden Information State model which does scale and which can be used to build practical systems. A prototype HIS system for the tourist information domain is evaluated and compared with a baseline MDP system using both user simulations and a live user trial. The results give strong support to the central contention that the POMDP-based framework is both a tractable and powerful approach to building more robust spoken dialogue systems. (C) 2009 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available