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2015

Learning to Mediate Perceptual Differences in Situated Human-Robot Dialogue

4 years 8 months ago
Learning to Mediate Perceptual Differences in Situated Human-Robot Dialogue
In human-robot dialogue, although a robot and its human partner are co-present in a shared environment, they have significantly mismatched perceptual capabilities (e.g., recognizing objects in the surroundings). When a shared perceptual basis is missing, it becomes difficult for the robot to identify referents in the physical world that are referred to by the human (i.e., a problem of referential grounding). To overcome this problem, we have developed an optimization based approach that allows the robot to detect and adapt to perceptual differences. Through online interaction with the human, the robot can learn a set of weights indicating how reliably/unreliably each dimension (e.g., object type, object color, etc.) of its perception of the environment maps to the human’s linguistic descriptors and thus adjust its word models accordingly. Our empirical evaluation has shown that this weight-learning approach can successfully adjust the weights to reflect the robot’s perceptual l...
Changsong Liu, Joyce Yue Chai
Added 27 Mar 2016
Updated 27 Mar 2016
Type Journal
Year 2015
Where AAAI
Authors Changsong Liu, Joyce Yue Chai
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