Following directions using statistical machine translation

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dc.contributor.authorMatuszek, Cynthia
dc.contributor.authorFox, Dieter
dc.contributor.authorKoscher, Karl
dc.date.accessioned2018-09-06T17:44:49Z
dc.date.available2018-09-06T17:44:49Z
dc.date.issued2010-04-22
dc.description© 2010 IEEE, 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)en_US
dc.description.abstractMobile robots that interact with humans in an intuitive way must be able to follow directions provided by humans in unconstrained natural language. In this work we investigate how statistical machine translation techniques can be used to bridge the gap between natural language route instructions and a map of an environment built by a robot. Our approach uses training data to learn to translate from natural language instructions to an automatically-labeled map. The complexity of the translation process is controlled by taking advantage of physical constraints imposed by the map. As a result, our technique can efficiently handle uncertainty in both map labeling and parsing. Our experiments demonstrate the promising capabilities achieved by our approach.en_US
dc.description.sponsorshipThe authors gratefully acknowledge the attendees of TCEP 16 for assistance obtaining sample route instructions and discussions of how to best present navigation routes.en_US
dc.description.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5453189&isnumber=5453161en_US
dc.format.extent8 PAGESen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M2K06X45K
dc.identifier.citationC. Matuszek, D. Fox and K. Koscher, "Following directions using statistical machine translation," 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Osaka, 2010, pp. 251-258.en_US
dc.identifier.uri10.1109/HRI.2010.5453189
dc.identifier.urihttp://hdl.handle.net/11603/11257
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectNatural languagesen_US
dc.subjectHumansen_US
dc.subjectMobile robotsen_US
dc.subjectBridgesen_US
dc.subjectRobotics and automationen_US
dc.subjectTraining dataen_US
dc.subjectAutomatic controlen_US
dc.subjectProcess controlen_US
dc.subjectUncertaintyen_US
dc.subjectLabelingen_US
dc.subjectInteractive Robotics and Language Laben_US
dc.titleFollowing directions using statistical machine translationen_US
dc.typeTexten_US

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