Unsupervised Selection of Negative Examples for Grounded Language Learning
dc.contributor.author | Pillai, Nisha | |
dc.contributor.author | Matuszek, Cynthia | |
dc.date.accessioned | 2018-09-05T20:56:56Z | |
dc.date.available | 2018-09-05T20:56:56Z | |
dc.date.issued | 2018-02 | |
dc.description | Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | en_US |
dc.description.abstract | There has been substantial work in recent years on grounded language acquisition, in which language and sensor data are used to create a model relating linguistic constructs to the perceivable world. While powerful, this approach is frequently hindered by ambiguities, redundancies, and omissions found in natural language. We describe an unsupervised system that learns language by training visual classifiers, first selecting important terms from object descriptions, then automatically choosing negative examples from a paired corpus of perceptual and linguistic data. We evaluate the effectiveness of each stage as well as the system's performance on the overall learning task. | en_US |
dc.description.sponsorship | This material is based upon work supported by the National Science Foundation under Grant No. 1657469. | en_US |
dc.description.uri | https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPaper/17440 | en_US |
dc.format.extent | 9 pages | en_US |
dc.genre | conference papers and proceedings preprints | en_US |
dc.identifier | doi:10.13016/M2WD3Q48B | |
dc.identifier.citation | Nisha Pillai, Cynthia Matuszek, Unsupervised Selection of Negative Examples for Grounded Language Learning, Thirty-Second AAAI Conference on Artificial Intelligence , 2018, https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPaper/17440 | en_US |
dc.identifier.uri | http://hdl.handle.net/11603/11241 | |
dc.language.iso | en_US | en_US |
dc.publisher | Association for the Advancement of Artificial Intelligence (AAAI) | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.rights | This 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.subject | robotics | en_US |
dc.subject | human-robot-interaction | en_US |
dc.subject | natural-language-processing | en_US |
dc.subject | Interactive Robotics and Language Lab | en_US |
dc.title | Unsupervised Selection of Negative Examples for Grounded Language Learning | en_US |
dc.type | Text | en_US |
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