@inproceedings{dutta-etal-2020-uds,
title = "{U}d{S}-{DFKI}@{WMT}20: Unsupervised {MT} and Very Low Resource Supervised {MT} for {G}erman-{U}pper {S}orbian",
author = "Dutta, Sourav and
Alabi, Jesujoba and
Bandyopadhyay, Saptarashmi and
Ruiter, Dana and
van Genabith, Josef",
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-1.129",
pages = "1092--1098",
abstract = "This paper describes the UdS-DFKI submission to the shared task for unsupervised machine translation (MT) and very low-resource supervised MT between German (de) and Upper Sorbian (hsb) at the Fifth Conference of Machine Translation (WMT20). We submit systems for both the supervised and unsupervised tracks. Apart from various experimental approaches like bitext mining, model pre-training, and iterative back-translation, we employ a factored machine translation approach on a small BPE vocabulary.",
}
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%0 Conference Proceedings
%T UdS-DFKI@WMT20: Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian
%A Dutta, Sourav
%A Alabi, Jesujoba
%A Bandyopadhyay, Saptarashmi
%A Ruiter, Dana
%A van Genabith, Josef
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F dutta-etal-2020-uds
%X This paper describes the UdS-DFKI submission to the shared task for unsupervised machine translation (MT) and very low-resource supervised MT between German (de) and Upper Sorbian (hsb) at the Fifth Conference of Machine Translation (WMT20). We submit systems for both the supervised and unsupervised tracks. Apart from various experimental approaches like bitext mining, model pre-training, and iterative back-translation, we employ a factored machine translation approach on a small BPE vocabulary.
%U https://aclanthology.org/2020.wmt-1.129
%P 1092-1098
Markdown (Informal)
[UdS-DFKI@WMT20: Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian](https://aclanthology.org/2020.wmt-1.129) (Dutta et al., WMT 2020)
ACL