Building Language-Agnostic Grounded Language Learning Systems

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dc.contributor.authorKery, Caroline
dc.contributor.authorPillai, Nisha
dc.contributor.authorMatuszek, Cynthia
dc.contributor.authorFerraro, Francis
dc.date.accessioned2019-10-04T14:32:26Z
dc.date.available2019-10-04T14:32:26Z
dc.date.issued2019
dc.description.abstractLearning the meaning of grounded language— language that references a robot’s physical environment and perceptual data—is an important and increasingly widely studied problem in robotics and human-robot interaction. However, with a few exceptions, research in robotics has focused on learning groundings for a single natural language pertaining to rich perceptual data. We present experiments on taking an existing natural language grounding system designed for English and applying it to a novel multilingual corpus of descriptions of objects paired with RGB-D perceptual data. We demonstrate that this specific approach transfers well to different languages, but also present possible design constraints to consider for grounded language learning systems intended for robots that will function in a variety of linguistic settingsen_US
dc.description.sponsorshipThis material is based in part upon work supported by the National Science Foundation under Grant No. 1657469en_US
dc.description.urihttp://iral.cs.umbc.edu/Pubs/KeryROMAN2019.pdfen_US
dc.format.extent7 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/m25vha-8wxj
dc.identifier.citationPillai, N., Matuszek, C., Ferraro, F., & Kery, C. (2019). Building Language-Agnostic Grounded Language Learning Systems.en_US
dc.identifier.urihttp://hdl.handle.net/11603/14975
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2019 IEEE.
dc.subjectgrounded languageen_US
dc.subjecthuman-robot interactionen_US
dc.subjectgrounded language learning systemsen_US
dc.titleBuilding Language-Agnostic Grounded Language Learning Systemsen_US
dc.typeTexten_US

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