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We propose a novel approach to developing a tractable affective dialogue model for probabilistic frame-based dialogue systems. The affective dialogue model, based on Partially Observable Markov Decision Process (POMDP) and Dynamic Decision Network (DDN) techniques, is composed of two main parts: the slot-level dialogue manager and the global dialogue manager. It has two new features: (1) being able to deal with a large number of slots and (2) being able to take into account some aspects of the user's affective state in deriving the adaptive dialogue strategies. Our implemented prototype dialogue manager can handle hundreds of slots, where each individual slot might have hundreds of values. Our approach is illustrated through a route navigation example in the crisis management domain. We conducted various experiments to evaluate our approach and to compare it with approximate POMDP techniques and handcrafted policies. The experimental results showed that the DDN–POMDP policy outperforms three handcrafted policies when the user's action error is induced by stress as well as when the observation error increases. Further, performance of the one-step look-ahead DDN–POMDP policy after optimizing its internal reward is close to state-of-the-art approximate POMDP counterparts.

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In current meeting research we see modest attempts to visualize the information that has been obtained by either capturing and probably more importantly by interpreting the activities that take place during a meeting. The meetings being considered take place in smart meeting rooms. Cameras, microphones and other sensors capture meeting activities. Captured information can be stored and retrieved. Captured information can also be manipulated and in turn displayed on different media. We survey our research in this area, look at issues that deal with turn-taking and gaze behavior of meeting participants, issues that deal with influence and talkativeness, and issues that deal with virtual embodied representations of meeting participants. We stress that this information is interesting not only for real-time meeting support, but also for remote participants and off-line consultation of meeting information.1