Title: Putting Things in Context: Situated Language Understanding for Human-Robot Dialog(ue)
Abstract: In this paper we present a model of language contextualization for spatially situated dialogue systems including service robots. The contextualization model addresses the problem of location sensitivity in language understanding for human-robot interaction. Our model is based on the application of situation-sensitive contextualization functions to a dialogue move’s semantic roles – both for the resolution of specified content and the augmentation of empty roles in cases of ellipsis. Unlike the previous use of default values, this methodology provides a context-dependent discourse process which reduces unnecessary artificial clarificatory statements. We detail this model and report on a number of user studies conducted with a simulated robotic system based on this model.
Publication Year: 2010
Publication Date: 2010-01-01
Language: en
Type: article
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Cited By Count: 1
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