@inproceedings{soares-vaz-2020-uos,
title = "{U}o{S} Participation in the {WMT}20 Translation of Biomedical Abstracts",
author = "Soares, Felipe and
Vaz, Delton",
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-1.95",
pages = "870--874",
abstract = "This paper describes the machine translation systems developed by the University of Sheffield (UoS) team for the biomedical translation shared task of WMT20. Our system is based on a Transformer model with TensorFlow Model Garden toolkit. We participated in ten translation directions for the English/Spanish, English/Portuguese, English/Russian, English/Italian, and English/French language pairs. To create our training data, we concatenated several parallel corpora, both from in-domain and out-of-domain sources.",
}
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<abstract>This paper describes the machine translation systems developed by the University of Sheffield (UoS) team for the biomedical translation shared task of WMT20. Our system is based on a Transformer model with TensorFlow Model Garden toolkit. We participated in ten translation directions for the English/Spanish, English/Portuguese, English/Russian, English/Italian, and English/French language pairs. To create our training data, we concatenated several parallel corpora, both from in-domain and out-of-domain sources.</abstract>
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%0 Conference Proceedings
%T UoS Participation in the WMT20 Translation of Biomedical Abstracts
%A Soares, Felipe
%A Vaz, Delton
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F soares-vaz-2020-uos
%X This paper describes the machine translation systems developed by the University of Sheffield (UoS) team for the biomedical translation shared task of WMT20. Our system is based on a Transformer model with TensorFlow Model Garden toolkit. We participated in ten translation directions for the English/Spanish, English/Portuguese, English/Russian, English/Italian, and English/French language pairs. To create our training data, we concatenated several parallel corpora, both from in-domain and out-of-domain sources.
%U https://aclanthology.org/2020.wmt-1.95
%P 870-874
Markdown (Informal)
[UoS Participation in the WMT20 Translation of Biomedical Abstracts](https://aclanthology.org/2020.wmt-1.95) (Soares & Vaz, WMT 2020)
ACL