In this paper we present a continual context-sensitive abductive framework for understanding situated spoken natural dialogue. The framework builds up and refines a set of partial defeasible explanations of the spoken input, trying to infer the speaker's intention. These partial explanations are conditioned on the eventual verification of the knowledge gaps they contain. This verification is done by executing test actions, thereby going beyond the initial context. The approach is illustrated by an example set in the context of human-robot interaction. © 2012 Springer-Verlag.
CITATION STYLE
Janíček, M. (2012). Abductive reasoning for continual dialogue understanding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7415 LNCS, pp. 16–31). https://doi.org/10.1007/978-3-642-31467-4_2
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