Journal ArticleDOI
POMDP-Based Statistical Spoken Dialog Systems: A Review
Steve Young,Milica Gasic,Blaise Thomson,Jason D. Williams +3 more
- Vol. 101, Iss: 5, pp 1160-1179
TLDR
This review article provides an overview of the current state of the art in the development of POMDP-based spoken dialog systems.Abstract:
Statistical dialog systems (SDSs) are motivated by the need for a data-driven framework that reduces the cost of laboriously handcrafting complex dialog managers and that provides robustness against the errors created by speech recognizers operating in noisy environments. By including an explicit Bayesian model of uncertainty and by optimizing the policy via a reward-driven process, partially observable Markov decision processes (POMDPs) provide such a framework. However, exact model representation and optimization is computationally intractable. Hence, the practical application of POMDP-based systems requires efficient algorithms and carefully constructed approximations. This review article provides an overview of the current state of the art in the development of POMDP-based spoken dialog systems.read more
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References
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