Enhancing Access to Online Education: Quality Machine Translation of MOOC Content

Valia Kordoni, Antal van den Bosch, Katia Lida Kermanidis, Vilelmini Sosoni, Kostadin Cholakov, Iris Hendrickx, Matthias Huck, Andy Way


Abstract
The present work is an overview of the TraMOOC (Translation for Massive Open Online Courses) research and innovation project, a machine translation approach for online educational content. More specifically, videolectures, assignments, and MOOC forum text is automatically translated from English into eleven European and BRIC languages. Unlike previous approaches to machine translation, the output quality in TraMOOC relies on a multimodal evaluation schema that involves crowdsourcing, error type markup, an error taxonomy for translation model comparison, and implicit evaluation via text mining, i.e. entity recognition and its performance comparison between the source and the translated text, and sentiment analysis on the students’ forum posts. Finally, the evaluation output will result in more and better quality in-domain parallel data that will be fed back to the translation engine for higher quality output. The translation service will be incorporated into the Iversity MOOC platform and into the VideoLectures.net digital library portal.
Anthology ID:
L16-1003
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
16–22
Language:
URL:
https://www.aclweb.org/anthology/L16-1003
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/L16-1003.pdf