Caglayan, O., Madhyastha, P., Specia, L. et al. (1 more author) (2019) Probing the need for visual context in multimodal machine translation. In: Burstein, J., Doran, C. and Solorio, T., (eds.) Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, 02-07 Jun 2019, Minneapolis, MN, USA. Association for Computational Linguistics , pp. 4159-4170.
Abstract
Current work on multimodal machine translation (MMT) has suggested that the visual modality is either unnecessary or only marginally beneficial. We posit that this is a consequence of the very simple, short and repetitive sentences used in the only available dataset for the task (Multi30K), rendering the source text sufficient as context. In the general case, however, we believe that it is possible to combine visual and textual information in order to ground translations. In this paper we probe the contribution of the visual modality to state-of-the-art MMT models by conducting a systematic analysis where we partially deprive the models from source-side textual context. Our results show that under limited textual context, models are capable of leveraging the visual input to generate better translations. This contradicts the current belief that MMT models disregard the visual modality because of either the quality of the image features or the way they are integrated into the model.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2019 Association for Computational Linguistics. This is an author-produced version of a paper subsequently published in the ACL Anthology. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Dec 2019 14:44 |
Last Modified: | 12 Dec 2019 22:21 |
Published Version: | https://www.aclweb.org/anthology/N19-1422.pdf |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Refereed: | Yes |
Identification Number: | 10.18653/v1/N19-1422 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154413 |