@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).",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="singh-etal-2020-nits">
    <titleInfo>
        <title>The NITS-CNLP System for the Unsupervised MT Task at WMT 2020</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Salam</namePart>
        <namePart type="given">Michael</namePart>
        <namePart type="family">Singh</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Thoudam</namePart>
        <namePart type="given">Doren</namePart>
        <namePart type="family">Singh</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sivaji</namePart>
        <namePart type="family">Bandyopadhyay</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-nov</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Fifth Conference on Machine Translation</title>
        </titleInfo>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <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).</abstract>
    <identifier type="citekey">singh-etal-2020-nits</identifier>
    <location>
        <url>https://aclanthology.org/2020.wmt-1.135</url>
    </location>
    <part>
        <date>2020-nov</date>
        <extent unit="page">
            <start>1139</start>
            <end>1143</end>
        </extent>
    </part>
</mods>
</modsCollection>
%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