@inproceedings{arnejsek-unk-2020-multidimensional,
title = "Multidimensional assessment of the e{T}ranslation output for {E}nglish{--}{S}lovene",
author = "Arnej{\v{s}}ek, Mateja and
Unk, Alenka",
editor = "Martins, Andr{\'e} and
Moniz, Helena and
Fumega, Sara and
Martins, Bruno and
Batista, Fernando and
Coheur, Luisa and
Parra, Carla and
Trancoso, Isabel and
Turchi, Marco and
Bisazza, Arianna and
Moorkens, Joss and
Guerberof, Ana and
Nurminen, Mary and
Marg, Lena and
Forcada, Mikel L.",
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
month = nov,
year = "2020",
address = "Lisboa, Portugal",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2020.eamt-1.41",
pages = "383--392",
abstract = "The Slovene language department of the European Commission Directorate-General for Translation has always been an early adopter of new developments in the area of machine translation. In 2018, the department started using neural machine translation produced by the eTranslation in-house engines. In 2019, a multidimensional assessment of the eTranslation output for the language combination English{--}Slovene was carried out. It was based on two user satisfaction surveys, an analysis of detected and reported errors and an ex post analysis of a sample. As part of the assessment effort, a categorisation of errors was devised in order to raise awareness among translators of the potential pitfalls of neural machine translation.",
}
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<abstract>The Slovene language department of the European Commission Directorate-General for Translation has always been an early adopter of new developments in the area of machine translation. In 2018, the department started using neural machine translation produced by the eTranslation in-house engines. In 2019, a multidimensional assessment of the eTranslation output for the language combination English–Slovene was carried out. It was based on two user satisfaction surveys, an analysis of detected and reported errors and an ex post analysis of a sample. As part of the assessment effort, a categorisation of errors was devised in order to raise awareness among translators of the potential pitfalls of neural machine translation.</abstract>
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%0 Conference Proceedings
%T Multidimensional assessment of the eTranslation output for English–Slovene
%A Arnejšek, Mateja
%A Unk, Alenka
%Y Martins, André
%Y Moniz, Helena
%Y Fumega, Sara
%Y Martins, Bruno
%Y Batista, Fernando
%Y Coheur, Luisa
%Y Parra, Carla
%Y Trancoso, Isabel
%Y Turchi, Marco
%Y Bisazza, Arianna
%Y Moorkens, Joss
%Y Guerberof, Ana
%Y Nurminen, Mary
%Y Marg, Lena
%Y Forcada, Mikel L.
%S Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
%D 2020
%8 November
%I European Association for Machine Translation
%C Lisboa, Portugal
%F arnejsek-unk-2020-multidimensional
%X The Slovene language department of the European Commission Directorate-General for Translation has always been an early adopter of new developments in the area of machine translation. In 2018, the department started using neural machine translation produced by the eTranslation in-house engines. In 2019, a multidimensional assessment of the eTranslation output for the language combination English–Slovene was carried out. It was based on two user satisfaction surveys, an analysis of detected and reported errors and an ex post analysis of a sample. As part of the assessment effort, a categorisation of errors was devised in order to raise awareness among translators of the potential pitfalls of neural machine translation.
%U https://aclanthology.org/2020.eamt-1.41
%P 383-392
Markdown (Informal)
[Multidimensional assessment of the eTranslation output for English–Slovene](https://aclanthology.org/2020.eamt-1.41) (Arnejšek & Unk, EAMT 2020)
ACL