<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="yang-etal-2021-tentrans">
    <titleInfo>
        <title>TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Han</namePart>
        <namePart type="family">Yang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Bojie</namePart>
        <namePart type="family">Hu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Wanying</namePart>
        <namePart type="family">Xie</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ambyera</namePart>
        <namePart type="family">Han</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Pan</namePart>
        <namePart type="family">Liu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jinan</namePart>
        <namePart type="family">Xu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Qi</namePart>
        <namePart type="family">Ju</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-nov</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Sixth 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>This paper describes TenTrans’ submission to WMT21 Multilingual Low-Resource Translation shared task for the Romance language pairs. This task focuses on improving translation quality from Catalan to Occitan, Romanian and Italian, with the assistance of related high-resource languages. We mainly utilize back-translation, pivot-based methods, multilingual models, pre-trained model fine-tuning, and in-domain knowledge transfer to improve the translation quality. On the test set, our best-submitted system achieves an average of 43.45 case-sensitive BLEU scores across all low-resource pairs. Our data, code, and pre-trained models used in this work are available in TenTrans evaluation examples.</abstract>
    <identifier type="citekey">yang-etal-2021-tentrans</identifier>
    <location>
        <url>https://aclanthology.org/2021.wmt-1.45</url>
    </location>
    <part>
        <date>2021-nov</date>
        <extent unit="page">
            <start>376</start>
            <end>382</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task
%A Yang, Han
%A Hu, Bojie
%A Xie, Wanying
%A Han, Ambyera
%A Liu, Pan
%A Xu, Jinan
%A Ju, Qi
%S Proceedings of the Sixth Conference on Machine Translation
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Online
%F yang-etal-2021-tentrans
%X This paper describes TenTrans’ submission to WMT21 Multilingual Low-Resource Translation shared task for the Romance language pairs. This task focuses on improving translation quality from Catalan to Occitan, Romanian and Italian, with the assistance of related high-resource languages. We mainly utilize back-translation, pivot-based methods, multilingual models, pre-trained model fine-tuning, and in-domain knowledge transfer to improve the translation quality. On the test set, our best-submitted system achieves an average of 43.45 case-sensitive BLEU scores across all low-resource pairs. Our data, code, and pre-trained models used in this work are available in TenTrans evaluation examples.
%U https://aclanthology.org/2021.wmt-1.45
%P 376-382

Markdown (Informal)

[TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task](https://aclanthology.org/2021.wmt-1.45) (Yang et al., WMT 2021)

• TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task (Yang et al., WMT 2021)

ACL

• Han Yang, Bojie Hu, Wanying Xie, Ambyera Han, Pan Liu, Jinan Xu, and Qi Ju. 2021. TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task. In Proceedings of the Sixth Conference on Machine Translation, pages 376–382, Online. Association for Computational Linguistics.