Improving machine translation of educational content via crowdsourcing

Autor: Behnke, M., Barone, A. V. M., Sennrich, R., Sosoni, V., Naskos, T., Takoulidou, E., Stasimioti, M., Menno van Zaanen, Castilho, S., Gaspari, F., Georgakopoulou, P., Kordoni, V., Egg, M., Kermanidis, K. L.

Publikováno v: Scopus-Elsevier
Behnke, Maximiliana, Miceli Barone, Antonio Valerio, Sennrich, Rico, Sosoni, Vilelmini, Naskos, Thanasis, Takoulidou, Eirini, Stasimioti, Maria, Menno, van Zaanen, Castilho, Sheila ORCID: 0000-0002-8416-6555 , Gaspari, Federico ORCID: 0000-0003-3808-8418 , Georgakopoulou, Panayota ORCID: 0000-0001-9780-1813 , Kordoni, Valia, Egg, Markus and Kermanidis, Katia Lida ORCID: 0000-0002-3270-5078 (2018) Improving machine translation of educational content via crowdsourcing. In: LREC 2018-11th International Conference on Language Resources and Evaluation, Miyazaki, Japan. ISBN 979-10-95546-19-1
Behnke, M, Miceli Barone, A V, Sennrich, R, Sosoni, V, Naskos, T, Takoulidou, E, Stasimioti, M, van Zaanan, M, Castilho, S, Gaspari, F, Georgakopoulou, P, Kordoni, V, Egg, M & Kermanidis, K L 2018, Improving Machine Translation of Educational Content via Crowdsourcing . in 11th Edition of the Language Resources and Evaluation Conference . Miyazaki, Japan, pp. 3343-3347, 11th Edition of the Language Resources and Evaluation Conference, Miyazaki, Japan, 7/05/18 . < http://www.lrec-conf.org/proceedings/lrec2018/summaries/855.html >

The limited availability of in-domain training data is a major issue in the training of application-specific neural machine translation models. Professional outsourcing of bilingual data collections is costly and often not feasible. In this paper we

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