The MeMAD Submission to the WMT18 Multimodal Translation Task
Stig-Arne Grönroos, Benoit Huet, Mikko Kurimo, Jorma Laaksonen, Bernard Merialdo, Phu Pham, Mats Sjöberg, Umut Sulubacak, Jörg Tiedemann, Raphael Troncy, Raúl Vázquez
Abstract
This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation Shared Task. We propose adapting the Transformer neural machine translation (NMT) architecture to a multi-modal setting. In this paper, we also describe the preliminary experiments with text-only translation systems leading us up to this choice. We have the top scoring system for both English-to-German and English-to-French, according to the automatic metrics for flickr18. Our experiments show that the effect of the visual features in our system is small. Our largest gains come from the quality of the underlying text-only NMT system. We find that appropriate use of additional data is effective.- Anthology ID:
- W18-6439
- Volume:
- Proceedings of the Third Conference on Machine Translation: Shared Task Papers
- Month:
- October
- Year:
- 2018
- Address:
- Belgium, Brussels
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 603–611
- Language:
- URL:
- https://aclanthology.org/W18-6439
- DOI:
- 10.18653/v1/W18-6439
- Bibkey:
- Cite (ACL):
- Stig-Arne Grönroos, Benoit Huet, Mikko Kurimo, Jorma Laaksonen, Bernard Merialdo, Phu Pham, Mats Sjöberg, Umut Sulubacak, Jörg Tiedemann, Raphael Troncy, and Raúl Vázquez. 2018. The MeMAD Submission to the WMT18 Multimodal Translation Task. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 603–611, Belgium, Brussels. Association for Computational Linguistics.
- Cite (Informal):
- The MeMAD Submission to the WMT18 Multimodal Translation Task (Grönroos et al., WMT 2018)
- Copy Citation:
- PDF:
- https://aclanthology.org/W18-6439.pdf
- Data
- MS COCO
Export citation
@inproceedings{gronroos-etal-2018-memad,
title = "The {M}e{MAD} Submission to the {WMT}18 Multimodal Translation Task",
author = {Gr{\"o}nroos, Stig-Arne and
Huet, Benoit and
Kurimo, Mikko and
Laaksonen, Jorma and
Merialdo, Bernard and
Pham, Phu and
Sj{\"o}berg, Mats and
Sulubacak, Umut and
Tiedemann, J{\"o}rg and
Troncy, Raphael and
V{\'a}zquez, Ra{\'u}l},
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Specia, Lucia and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
month = oct,
year = "2018",
address = "Belgium, Brussels",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6439",
doi = "10.18653/v1/W18-6439",
pages = "603--611",
abstract = "This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation Shared Task. We propose adapting the Transformer neural machine translation (NMT) architecture to a multi-modal setting. In this paper, we also describe the preliminary experiments with text-only translation systems leading us up to this choice. We have the top scoring system for both English-to-German and English-to-French, according to the automatic metrics for flickr18. Our experiments show that the effect of the visual features in our system is small. Our largest gains come from the quality of the underlying text-only NMT system. We find that appropriate use of additional data is effective.",
}
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%0 Conference Proceedings %T The MeMAD Submission to the WMT18 Multimodal Translation Task %A Grönroos, Stig-Arne %A Huet, Benoit %A Kurimo, Mikko %A Laaksonen, Jorma %A Merialdo, Bernard %A Pham, Phu %A Sjöberg, Mats %A Sulubacak, Umut %A Tiedemann, Jörg %A Troncy, Raphael %A Vázquez, Raúl %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Specia, Lucia %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Third Conference on Machine Translation: Shared Task Papers %D 2018 %8 October %I Association for Computational Linguistics %C Belgium, Brussels %F gronroos-etal-2018-memad %X This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation Shared Task. We propose adapting the Transformer neural machine translation (NMT) architecture to a multi-modal setting. In this paper, we also describe the preliminary experiments with text-only translation systems leading us up to this choice. We have the top scoring system for both English-to-German and English-to-French, according to the automatic metrics for flickr18. Our experiments show that the effect of the visual features in our system is small. Our largest gains come from the quality of the underlying text-only NMT system. We find that appropriate use of additional data is effective. %R 10.18653/v1/W18-6439 %U https://aclanthology.org/W18-6439 %U https://doi.org/10.18653/v1/W18-6439 %P 603-611
Markdown (Informal)
[The MeMAD Submission to the WMT18 Multimodal Translation Task](https://aclanthology.org/W18-6439) (Grönroos et al., WMT 2018)
- The MeMAD Submission to the WMT18 Multimodal Translation Task (Grönroos et al., WMT 2018)
ACL
- Stig-Arne Grönroos, Benoit Huet, Mikko Kurimo, Jorma Laaksonen, Bernard Merialdo, Phu Pham, Mats Sjöberg, Umut Sulubacak, Jörg Tiedemann, Raphael Troncy, and Raúl Vázquez. 2018. The MeMAD Submission to the WMT18 Multimodal Translation Task. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 603–611, Belgium, Brussels. Association for Computational Linguistics.