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NIFTi is about human-robot cooperation. About teams of robots and humans doing tasks together, interacting together to try and reach a shared goal. NIFTi looks at how the robot could bear the human in mind. Literally. When determining what to do or say next in human-robot interaction; when, and how. NIFTi puts the human factor into cognitive robots, and human-robot team interaction in particular.   Each year, NIFTi evaluates its systems together with several USAR organizations. Rescue personnel teams up with NIFTi robots to carry out realistic missions, in real-life training areas. 
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Geert-Jan Kruijff and Hans-Ulrich Krieger (2010)

Learnable Controllers for Adaptive Dialogue Processing Management

In: Proceedings of the AAAI 2010 Fall Symposium "Dialogue with Robots".

The paper focuses on how a model could be learnt for determining at runtime how much of spoken input needs to be understood, and what configuration of processes can be expected to yield that result. Typically, a dialogue system applies a fixed configuration of shallow and deep forms of processing to its input. The configuration tries to balance robustness with depth of understanding, creating a system that always tries to understand as well as it can. The paper adopts a different view, assuming that what needs to be understood can vary per context. To facilitate this any-depth processing, the paper proposes an approach based on learnable controllers. The paper illustrates the main ideas of the approach on examples from a robot acquiring situated dialogue competence, and a robot working with users on a task.
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