@inproceedings{singh-etal-2020-nits,
title = "The {NITS}-{CNLP} System for the Unsupervised {MT} Task at {WMT} 2020",
author = "Singh, Salam Michael and
Singh, Thoudam Doren and
Bandyopadhyay, Sivaji",
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-1.135",
pages = "1139--1143",
abstract = "We describe NITS-CNLP{'}s submission to WMT 2020 unsupervised machine translation shared task for German language (de) to Upper Sorbian (hsb) in a constrained setting i.e, using only the data provided by the organizers. We train our unsupervised model using monolingual data from both the languages by jointly pre-training the encoder and decoder and fine-tune using backtranslation loss. The final model uses the source side (de) monolingual data and the target side (hsb) synthetic data as a pseudo-parallel data to train a pseudo-supervised system which is tuned using the provided development set(dev set).",
}
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%0 Conference Proceedings
%T The NITS-CNLP System for the Unsupervised MT Task at WMT 2020
%A Singh, Salam Michael
%A Singh, Thoudam Doren
%A Bandyopadhyay, Sivaji
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F singh-etal-2020-nits
%X We describe NITS-CNLP’s submission to WMT 2020 unsupervised machine translation shared task for German language (de) to Upper Sorbian (hsb) in a constrained setting i.e, using only the data provided by the organizers. We train our unsupervised model using monolingual data from both the languages by jointly pre-training the encoder and decoder and fine-tune using backtranslation loss. The final model uses the source side (de) monolingual data and the target side (hsb) synthetic data as a pseudo-parallel data to train a pseudo-supervised system which is tuned using the provided development set(dev set).
%U https://aclanthology.org/2020.wmt-1.135
%P 1139-1143
Markdown (Informal)
[The NITS-CNLP System for the Unsupervised MT Task at WMT 2020](https://aclanthology.org/2020.wmt-1.135) (Singh et al., WMT 2020)
ACL