@inproceedings{garcia-martinez-etal-2021-neural,
title = "Neural Translation for {E}uropean {U}nion ({NTEU})",
author = "Garc{\'\i}a-Mart{\'\i}nez, Mercedes and
Bi{\'e}, Laurent and
Cerd{\`a}, Aleix and
Estela, Amando and
Herranz, Manuel and
Kri{\v{s}}lauks, Rihards and
Melero, Maite and
O{'}Dowd, Tony and
O{'}Gorman, Sinead and
Pinnis, Marcis and
Stafanovi{\v{c}}, Art{\=u}rs and
Superbo, Riccardo and
Vasi{\c{l}}evskis, Art{\=u}rs",
editor = "Campbell, Janice and
Huyck, Ben and
Larocca, Stephen and
Marciano, Jay and
Savenkov, Konstantin and
Yanishevsky, Alex",
booktitle = "Proceedings of Machine Translation Summit XVIII: Users and Providers Track",
month = aug,
year = "2021",
address = "Virtual",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2021.mtsummit-up.23",
pages = "316--334",
abstract = "The Neural Translation for the European Union (NTEU) engine farm enables direct machine translation for all 24 official languages of the European Union without the necessity to use a high-resourced language as a pivot. This amounts to a total of 552 translation engines for all combinations of the 24 languages. We have collected parallel data for all the language combinations publickly shared in elrc-share.eu. The translation engines have been customized to domain,for the use of the European public administrations. The delivered engines will be published in the European Language Grid. In addition to the usual automatic metrics, all the engines have been evaluated by humans based on the direct assessment methodology. For this purpose, we built an open-source platform called MTET The evaluation shows that most of the engines reach high quality and get better scores compared to an external machine translation service in a blind evaluation setup.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="garcia-martinez-etal-2021-neural">
<titleInfo>
<title>Neural Translation for European Union (NTEU)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Mercedes</namePart>
<namePart type="family">García-Martínez</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Laurent</namePart>
<namePart type="family">Bié</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aleix</namePart>
<namePart type="family">Cerdà</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Amando</namePart>
<namePart type="family">Estela</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Manuel</namePart>
<namePart type="family">Herranz</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rihards</namePart>
<namePart type="family">Krišlauks</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Maite</namePart>
<namePart type="family">Melero</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tony</namePart>
<namePart type="family">O’Dowd</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sinead</namePart>
<namePart type="family">O’Gorman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marcis</namePart>
<namePart type="family">Pinnis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Artūrs</namePart>
<namePart type="family">Stafanovič</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Riccardo</namePart>
<namePart type="family">Superbo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Artūrs</namePart>
<namePart type="family">Vasiļevskis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of Machine Translation Summit XVIII: Users and Providers Track</title>
</titleInfo>
<name type="personal">
<namePart type="given">Janice</namePart>
<namePart type="family">Campbell</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ben</namePart>
<namePart type="family">Huyck</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stephen</namePart>
<namePart type="family">Larocca</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jay</namePart>
<namePart type="family">Marciano</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Konstantin</namePart>
<namePart type="family">Savenkov</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alex</namePart>
<namePart type="family">Yanishevsky</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Machine Translation in the Americas</publisher>
<place>
<placeTerm type="text">Virtual</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>The Neural Translation for the European Union (NTEU) engine farm enables direct machine translation for all 24 official languages of the European Union without the necessity to use a high-resourced language as a pivot. This amounts to a total of 552 translation engines for all combinations of the 24 languages. We have collected parallel data for all the language combinations publickly shared in elrc-share.eu. The translation engines have been customized to domain,for the use of the European public administrations. The delivered engines will be published in the European Language Grid. In addition to the usual automatic metrics, all the engines have been evaluated by humans based on the direct assessment methodology. For this purpose, we built an open-source platform called MTET The evaluation shows that most of the engines reach high quality and get better scores compared to an external machine translation service in a blind evaluation setup.</abstract>
<identifier type="citekey">garcia-martinez-etal-2021-neural</identifier>
<location>
<url>https://aclanthology.org/2021.mtsummit-up.23</url>
</location>
<part>
<date>2021-08</date>
<extent unit="page">
<start>316</start>
<end>334</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Neural Translation for European Union (NTEU)
%A García-Martínez, Mercedes
%A Bié, Laurent
%A Cerdà, Aleix
%A Estela, Amando
%A Herranz, Manuel
%A Krišlauks, Rihards
%A Melero, Maite
%A O’Dowd, Tony
%A O’Gorman, Sinead
%A Pinnis, Marcis
%A Stafanovič, Artūrs
%A Superbo, Riccardo
%A Vasiļevskis, Artūrs
%Y Campbell, Janice
%Y Huyck, Ben
%Y Larocca, Stephen
%Y Marciano, Jay
%Y Savenkov, Konstantin
%Y Yanishevsky, Alex
%S Proceedings of Machine Translation Summit XVIII: Users and Providers Track
%D 2021
%8 August
%I Association for Machine Translation in the Americas
%C Virtual
%F garcia-martinez-etal-2021-neural
%X The Neural Translation for the European Union (NTEU) engine farm enables direct machine translation for all 24 official languages of the European Union without the necessity to use a high-resourced language as a pivot. This amounts to a total of 552 translation engines for all combinations of the 24 languages. We have collected parallel data for all the language combinations publickly shared in elrc-share.eu. The translation engines have been customized to domain,for the use of the European public administrations. The delivered engines will be published in the European Language Grid. In addition to the usual automatic metrics, all the engines have been evaluated by humans based on the direct assessment methodology. For this purpose, we built an open-source platform called MTET The evaluation shows that most of the engines reach high quality and get better scores compared to an external machine translation service in a blind evaluation setup.
%U https://aclanthology.org/2021.mtsummit-up.23
%P 316-334
Markdown (Informal)
[Neural Translation for European Union (NTEU)](https://aclanthology.org/2021.mtsummit-up.23) (García-Martínez et al., MTSummit 2021)
ACL
- Mercedes García-Martínez, Laurent Bié, Aleix Cerdà, Amando Estela, Manuel Herranz, Rihards Krišlauks, Maite Melero, Tony O’Dowd, Sinead O’Gorman, Marcis Pinnis, Artūrs Stafanovič, Riccardo Superbo, and Artūrs Vasiļevskis. 2021. Neural Translation for European Union (NTEU). In Proceedings of Machine Translation Summit XVIII: Users and Providers Track, pages 316–334, Virtual. Association for Machine Translation in the Americas.