Using Language Groundings for Context-Sensitive Text Prediction
| dc.contributor.author | Lewis, Timothy | |
| dc.contributor.author | Hurst, Amy | |
| dc.contributor.author | Taylor, Matthew E. | |
| dc.contributor.author | Matuszek, Cynthia | |
| dc.date.accessioned | 2018-09-06T17:42:38Z | |
| dc.date.available | 2018-09-06T17:42:38Z | |
| dc.date.issued | 2016 | |
| dc.description | EMNLP Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods, 2016 | |
| dc.description.abstract | In this paper, we present the concept of using language groundings for context sensitive text prediction using a semantically informed, context-aware language model. We show initial findings from a preliminary study investigating how users react to a communication interface driven by context-based prediction using a simple language model. We suggest that the results support further exploration using a more informed semantic model and more realistic context. | en_US |
| dc.description.uri | http://iral.cs.umbc.edu/Pubs/LewisEMNLP2016_uphill-workshop.pdf | |
| dc.format.extent | 5 PAGES | en_US |
| dc.genre | conference papers and proceedings preprints | en_US |
| dc.identifier | doi:10.13016/M26Q1SM35 | |
| dc.identifier.citation | Timothy Lewis, Amy Hurst, Matthew E. Taylor, & Cynthia Matuszek, Using Language Groundings for Context-Sensitive Text Prediction, EMNLP Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods, 2016; | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/11252 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Association for Computational Linguistics | 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.relation.ispartof | UMBC Student 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 | Grounded language | en_US |
| dc.subject | context sensitive generation | en_US |
| dc.subject | predictive text | en_US |
| dc.subject | Interactive Robotics and Language Lab | en_US |
| dc.title | Using Language Groundings for Context-Sensitive Text Prediction | en_US |
| dc.type | Text | en_US |