Reading comprehension of machine translation output: what makes
for a better read?
Castilho, SheilaORCID: 0000-0002-8416-6555 and Guerberof Arenas, AnaORCID: 0000-0001-9820-7074
(2018)
Reading comprehension of machine translation output: what makes
for a better read?
In: 21st Annual Conference of the European for Machine Translation, 28-30 May 2018, Alacant/Alicante, Spain.
ISBN 978-84-09-01901-4
This paper reports on a pilot experiment
that compares two different machine translation (MT) paradigms in reading comprehension tests. To explore a suitable
methodology, we set up a pilot experiment with a group of six users (with English, Spanish and Simplified Chinese languages) using an English Language Testing System (IELTS), and an eye-tracker.
The users were asked to read three texts
in their native language: either the original
English text (for the English speakers) or
the machine-translated text (for the Spanish and Simplified Chinese speakers). The
original texts were machine-translated via
two MT systems: neural (NMT) and statistical (SMT). The users were also asked
to rank satisfaction statements on a 3-point
scale after reading each text and answering
the respective comprehension questions.
After all tasks were completed, a post-task
retrospective interview took place to gather
qualitative data. The findings suggest that
the users from the target languages completed more tasks in less time with a higher
level of satisfaction when using translations from the NMT system.
Pérez-Ortiz, Juan Antonio, Sánchez-Martínez, Felipe, Esplá-Gomis, Miquel and Popović, Maja, (eds.)
Proceedings of the 21st Annual Conference of the European Association for Machine Translation.
.
21st Annual Conference of the European Association for Machine Translation. ISBN 978-84-09-01901-4
Publisher:
21st Annual Conference of the European Association for Machine Translation
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
European Unions Horizon 2020 and innovation programme under the Marie Sklodowska-Curie grant agreement No. 713567, SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund
ID Code:
23071
Deposited On:
08 Mar 2019 14:41 by
Thomas Murtagh
. Last Modified 26 May 2023 15:45