DocumentCode :
3526082
Title :
Learning environmental knowledge from task-based human-robot dialog
Author :
Kollar, Thomas ; Perera, Viraga ; Nardi, Damiano ; Veloso, Marco
Author_Institution :
Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2013
fDate :
6-10 May 2013
Firstpage :
4304
Lastpage :
4309
Abstract :
This paper presents an approach for learning environmental knowledge from task-based human-robot dialog. Previous approaches to dialog use domain knowledge to constrain the types of language people are likely to use. In contrast, by introducing a joint probabilistic model over speech, the resulting semantic parse and the mapping from each element of the parse to a physical entity in the building (e.g., grounding), our approach is flexible to the ways that untrained people interact with robots, is robust to speech to text errors and is able to learn referring expressions for physical locations in a map (e.g., to create a semantic map). Our approach has been evaluated by having untrained people interact with a service robot. Starting with an empty semantic map, our approach is able ask 50% fewer questions than a baseline approach, thereby enabling more effective and intuitive human robot dialog.
Keywords :
control engineering computing; human-robot interaction; interactive systems; learning (artificial intelligence); mobile robots; probability; semantic networks; service robots; speech synthesis; domain knowledge; empty semantic map; joint probabilistic model; learning environmental knowledge; physical entity; semantic parse; service robot; speech to text errors; task-based human-robot dialog; untrained people; Grounding; Knowledge based systems; Natural languages; Robots; Semantics; Speech; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2013 IEEE International Conference on
Conference_Location :
Karlsruhe
ISSN :
1050-4729
Print_ISBN :
978-1-4673-5641-1
Type :
conf
DOI :
10.1109/ICRA.2013.6631186
Filename :
6631186
Link To Document :
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