@inproceedings{brockmann-etal-2022-error,
title = "Error Annotation in Post-Editing Machine Translation: Investigating the Impact of Text-to-Speech Technology",
author = "Brockmann, Justus and
Wiesinger, Claudia and
Ciobanu, Dragoș",
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-1.28/",
pages = "251--259",
abstract = "As post-editing of machine translation (PEMT) is becoming one of the most dominant services offered by the language services industry (LSI), efforts are being made to support provision of this service with additional technology. We present text-to-speech (T2S) as a potential attention-raising technology for post-editors. Our study was conducted with university students and included both PEMT and error annotation of a creative text with and without T2S. Focusing on the error annotation data, our analysis finds that participants under-annotated fewer MT errors in the T2S condition compared to the silent condition. At the same time, more over-annotation was recorded. Finally, annotation performance corresponds to participants' attitudes towards using T2S."
}
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%0 Conference Proceedings
%T Error Annotation in Post-Editing Machine Translation: Investigating the Impact of Text-to-Speech Technology
%A Brockmann, Justus
%A Wiesinger, Claudia
%A Ciobanu, Dragoș
%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 brockmann-etal-2022-error
%X As post-editing of machine translation (PEMT) is becoming one of the most dominant services offered by the language services industry (LSI), efforts are being made to support provision of this service with additional technology. We present text-to-speech (T2S) as a potential attention-raising technology for post-editors. Our study was conducted with university students and included both PEMT and error annotation of a creative text with and without T2S. Focusing on the error annotation data, our analysis finds that participants under-annotated fewer MT errors in the T2S condition compared to the silent condition. At the same time, more over-annotation was recorded. Finally, annotation performance corresponds to participants’ attitudes towards using T2S.
%U https://aclanthology.org/2022.eamt-1.28/
%P 251-259
Markdown (Informal)
[Error Annotation in Post-Editing Machine Translation: Investigating the Impact of Text-to-Speech Technology](https://aclanthology.org/2022.eamt-1.28/) (Brockmann et al., EAMT 2022)
ACL