Sciweavers

Share
HRI
2010
ACM

Robust spoken instruction understanding for HRI

11 years 8 months ago
Robust spoken instruction understanding for HRI
—Natural human-robot interaction requires different and more robust models of language understanding (NLU) than non-embodied NLU systems. In particular, architectures are required that (1) process language incrementally in order to be able to provide early backchannel feedback to human speakers; (2) use pragmatic contexts throughout the understanding process to infer missing information; and (3) handle the underspecified, fragmentary, or otherwise ungrammatical utterances that are common in spontaneous speech. In this paper, we describe our attempts at developing an integrated natural language understanding architecture for HRI, and demonstrate its novel capabilities using challenging data collected in human-human interaction experiments. Keywords-natural human-robot interaction; natural language processing; dialogue interactions; integrated architecture
Rehj Cantrell, Matthias Scheutz, Paul W. Schermerh
Added 17 May 2010
Updated 17 May 2010
Type Conference
Year 2010
Where HRI
Authors Rehj Cantrell, Matthias Scheutz, Paul W. Schermerhorn, Xuan Wu
Comments (0)
books