Abstract
The effect of translationese has been studied in the field of machine translation (MT), mostly with respect to training data. We study in depth the effect of translationese on test data, using the test sets from the last three editions of WMT’s news shared task, containing 17 translation directions. We show evidence that (i) the use of translationese in test sets results in inflated human evaluation scores for MT systems; (ii) in some cases system rankings do change and (iii) the impact translationese has on a translation direction is inversely correlated to the translation quality attainable by state-of-the-art MT systems for that direction.- Anthology ID:
- W19-5208
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)
- 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:
- 73–81
- Language:
- URL:
- https://aclanthology.org/W19-5208
- DOI:
- 10.18653/v1/W19-5208
- Cite (ACL):
- Mike Zhang and Antonio Toral. 2019. The Effect of Translationese in Machine Translation Test Sets. In Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers), pages 73–81, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The Effect of Translationese in Machine Translation Test Sets (Zhang & Toral, WMT 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-5208.pdf
- Code
- jjzha/translationese
- Data
- WMT 2016