Bayesian update of dialogue state for robust dialogue systems

This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian network that represents the underlying state of a partially observable Markov decision process (POMDP). POMDP models provide a principled approach to handling uncertainty in dialogue but generally scale poorly with the size… CONTINUE READING

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