Do You See What I Mean? Visual Resolution of Linguistic Ambiguities
March 26, 2016 Β· Declared Dead Β· π Conference on Empirical Methods in Natural Language Processing
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Authors
Yevgeni Berzak, Andrei Barbu, Daniel Harari, Boris Katz, Shimon Ullman
arXiv ID
1603.08079
Category
cs.CV: Computer Vision
Cross-listed
cs.AI,
cs.CL
Citations
35
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
5 months ago
Abstract
Understanding language goes hand in hand with the ability to integrate complex contextual information obtained via perception. In this work, we present a novel task for grounded language understanding: disambiguating a sentence given a visual scene which depicts one of the possible interpretations of that sentence. To this end, we introduce a new multimodal corpus containing ambiguous sentences, representing a wide range of syntactic, semantic and discourse ambiguities, coupled with videos that visualize the different interpretations for each sentence. We address this task by extending a vision model which determines if a sentence is depicted by a video. We demonstrate how such a model can be adjusted to recognize different interpretations of the same underlying sentence, allowing to disambiguate sentences in a unified fashion across the different ambiguity types.
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