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EvalD Reference-Less Discourse Evaluation for WMT18

Ondřej Bojar, Jiří Mírovský, Kateřina Rysová, Magdaléna Rysová


Abstract
We present the results of automatic evaluation of discourse in machine translation (MT) outputs using the EVALD tool. EVALD was originally designed and trained to assess the quality of human writing, for native speakers and foreign-language learners. MT has seen a tremendous leap in translation quality at the level of sentences and it is thus interesting to see if the human-level evaluation is becoming relevant.
Anthology ID:
W18-6432
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Editors:
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
541–545
Language:
URL:
https://aclanthology.org/W18-6432
DOI:
10.18653/v1/W18-6432
Bibkey:
Cite (ACL):
Ondřej Bojar, Jiří Mírovský, Kateřina Rysová, and Magdaléna Rysová. 2018. EvalD Reference-Less Discourse Evaluation for WMT18. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 541–545, Belgium, Brussels. Association for Computational Linguistics.
Cite (Informal):
EvalD Reference-Less Discourse Evaluation for WMT18 (Bojar et al., WMT 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6432.pdf