@inproceedings{alva-manchego-shardlow-2022-towards,
title = "Towards Readability-Controlled Machine Translation of {COVID}-19 Texts",
author = "Alva-Manchego, Fernando and
Shardlow, Matthew",
editor = {Moniz, Helena and
Macken, Lieve and
Rufener, Andrew and
Barrault, Lo{\"\i}c and
Costa-juss{\`a}, Marta R. and
Declercq, Christophe and
Koponen, Maarit and
Kemp, Ellie and
Pilos, Spyridon and
Forcada, Mikel L. and
Scarton, Carolina and
Van den Bogaert, Joachim and
Daems, Joke and
Tezcan, Arda and
Vanroy, Bram and
Fonteyne, Margot},
booktitle = "Proceedings of the 23rd Annual Conference of the European Association for Machine Translation",
month = jun,
year = "2022",
address = "Ghent, Belgium",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2022.eamt-1.33",
pages = "287--288",
abstract = "This project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate this information, the resulting text may contain specialised terminology, or may be written in a style that is difficult for lay readers to understand. So far, we have collected a new dataset with manual simplifications for English and Spanish sentences in the TICO-19 dataset, as well as implemented baseline pipelines combining Machine Translation and Text Simplification models.",
}
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<abstract>This project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate this information, the resulting text may contain specialised terminology, or may be written in a style that is difficult for lay readers to understand. So far, we have collected a new dataset with manual simplifications for English and Spanish sentences in the TICO-19 dataset, as well as implemented baseline pipelines combining Machine Translation and Text Simplification models.</abstract>
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%0 Conference Proceedings
%T Towards Readability-Controlled Machine Translation of COVID-19 Texts
%A Alva-Manchego, Fernando
%A Shardlow, Matthew
%Y Moniz, Helena
%Y Macken, Lieve
%Y Rufener, Andrew
%Y Barrault, Loïc
%Y Costa-jussà, Marta R.
%Y Declercq, Christophe
%Y Koponen, Maarit
%Y Kemp, Ellie
%Y Pilos, Spyridon
%Y Forcada, Mikel L.
%Y Scarton, Carolina
%Y Van den Bogaert, Joachim
%Y Daems, Joke
%Y Tezcan, Arda
%Y Vanroy, Bram
%Y Fonteyne, Margot
%S Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
%D 2022
%8 June
%I European Association for Machine Translation
%C Ghent, Belgium
%F alva-manchego-shardlow-2022-towards
%X This project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate this information, the resulting text may contain specialised terminology, or may be written in a style that is difficult for lay readers to understand. So far, we have collected a new dataset with manual simplifications for English and Spanish sentences in the TICO-19 dataset, as well as implemented baseline pipelines combining Machine Translation and Text Simplification models.
%U https://aclanthology.org/2022.eamt-1.33
%P 287-288
Markdown (Informal)
[Towards Readability-Controlled Machine Translation of COVID-19 Texts](https://aclanthology.org/2022.eamt-1.33) (Alva-Manchego & Shardlow, EAMT 2022)
ACL