Abstract
We introduce a novel algorithm for generating referring expressions, informed by human and computer vision and designed to refer to visible objects. Our method separates absolute properties like color from relative properties like size to stochastically generate a diverse set of outputs. Expressions generated using this method are often overspecified and may be underspecified, akin to expressions produced by people. We call such expressions identifying descriptions. The algorithm outperforms the well-known Incremental Algorithm (Dale and Reiter, 1995) and the Graph- Based Algorithm (Krahmer et al., 2003; Viethen et al., 2008) across a variety of images in two domains. We additionally motivate an evaluation method for referring expression generation that takes the proposed algorithm's non-determinism into account.
Original language | English |
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Title of host publication | Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics |
Subtitle of host publication | Human Language Technologies |
Editors | Lucy Vanderwende, Hal Daumé III, Katrin Kirchhoff |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 1174-1184 |
Number of pages | 11 |
ISBN (Print) | 9781937284473 |
Publication status | Published - Jun 2013 |
Event | 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2013 - Atlanta, United States Duration: 9 Jun 2013 → 14 Jun 2013 |
Conference
Conference | 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2013 |
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Country/Territory | United States |
City | Atlanta |
Period | 9/06/13 → 14/06/13 |