Abstract
Machine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In this paper, we present the details of our submission to the WMT20 Chat Translation Task, which consists of two language directions, English –> German and German –> English. The major feature of our system is applying a pre-trained BERT embedding with a bidirectional recurrent neural network. Our system ensembles three models, each with different hyperparameters. Despite being trained on a very small corpus, our model produces surprisingly good results.- Anthology ID:
- 2020.wmt-1.59
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 479–482
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.59
- DOI:
- Bibkey:
- Cite (ACL):
- Roweida Mohammed, Mahmoud Al-Ayyoub, and Malak Abdullah. 2020. JUST System for WMT20 Chat Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 479–482, Online. Association for Computational Linguistics.
- Cite (Informal):
- JUST System for WMT20 Chat Translation Task (Mohammed et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.59.pdf
- Video:
- https://slideslive.com/38939629
Export citation
@inproceedings{mohammed-etal-2020-just,
title = "{JUST} System for {WMT}20 Chat Translation Task",
author = "Mohammed, Roweida and
Al-Ayyoub, Mahmoud and
Abdullah, Malak",
editor = {Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.59",
pages = "479--482",
abstract = "Machine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In this paper, we present the details of our submission to the WMT20 Chat Translation Task, which consists of two language directions, English {--}{\textgreater} German and German {--}{\textgreater} English. The major feature of our system is applying a pre-trained BERT embedding with a bidirectional recurrent neural network. Our system ensembles three models, each with different hyperparameters. Despite being trained on a very small corpus, our model produces surprisingly good results.",
}
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<abstract>Machine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In this paper, we present the details of our submission to the WMT20 Chat Translation Task, which consists of two language directions, English –\textgreater German and German –\textgreater English. The major feature of our system is applying a pre-trained BERT embedding with a bidirectional recurrent neural network. Our system ensembles three models, each with different hyperparameters. Despite being trained on a very small corpus, our model produces surprisingly good results.</abstract>
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%0 Conference Proceedings %T JUST System for WMT20 Chat Translation Task %A Mohammed, Roweida %A Al-Ayyoub, Mahmoud %A Abdullah, Malak %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F mohammed-etal-2020-just %X Machine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In this paper, we present the details of our submission to the WMT20 Chat Translation Task, which consists of two language directions, English –\textgreater German and German –\textgreater English. The major feature of our system is applying a pre-trained BERT embedding with a bidirectional recurrent neural network. Our system ensembles three models, each with different hyperparameters. Despite being trained on a very small corpus, our model produces surprisingly good results. %U https://aclanthology.org/2020.wmt-1.59 %P 479-482
Markdown (Informal)
[JUST System for WMT20 Chat Translation Task](https://aclanthology.org/2020.wmt-1.59) (Mohammed et al., WMT 2020)
- JUST System for WMT20 Chat Translation Task (Mohammed et al., WMT 2020)
ACL
- Roweida Mohammed, Mahmoud Al-Ayyoub, and Malak Abdullah. 2020. JUST System for WMT20 Chat Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 479–482, Online. Association for Computational Linguistics.