A Bayesian NETWORKS approach for dialog modeling: The fusion BN

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A Bayesian NETWORKS approach for dialog modeling: The fusion BN
Bayesian Networks, BNs, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. This solution can be applied to identify the intention of the user considering the concepts extracted from the last utterance and the dialog context. Subsequently, in order to make a correct decision regarding how the dialog should continue, unnecessary, missing, wrong, optional and required concepts have to be detected according to the inferred goals. This information is useful to properly drive the dialog prompting for missing concepts, clarifying for wrong concepts, ignoring unnecessary concepts and retrieving those required and optional. This paper presents a novel BNs approach where a single BN is obtained from N goal-specific BNs through a fusion process. The new fusion BN enables a single concept analysis which is more consistent with the whole dialog context.
Fernando F. Fernández-Martínez, Javi
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Authors Fernando F. Fernández-Martínez, Javier Ferreiros, Ricardo de Córdoba, Juan Manuel Montero, Rubén San Segundo, Jose Manuel M. Pardo
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