Machine Translation from an Intercomprehension Perspective

Yu Chen, Tania Avgustinova


Abstract
Within the first shared task on machine translation between similar languages, we present our first attempts on Czech to Polish machine translation from an intercomprehension perspective. We propose methods based on the mutual intelligibility of the two languages, taking advantage of their orthographic and phonological similarity, in the hope to improve over our baselines. The translation results are evaluated using BLEU. On this metric, none of our proposals could outperform the baselines on the final test set. The current setups are rather preliminary, and there are several potential improvements we can try in the future.
Anthology ID:
W19-5425
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
192–196
Language:
URL:
https://aclanthology.org/W19-5425
DOI:
10.18653/v1/W19-5425
Bibkey:
Cite (ACL):
Yu Chen and Tania Avgustinova. 2019. Machine Translation from an Intercomprehension Perspective. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 192–196, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Machine Translation from an Intercomprehension Perspective (Chen & Avgustinova, WMT 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-1/W19-5425.pdf