Applying the Cognitive Machine Translation Evaluation Approach to Arabic

Irina Temnikova, Wajdi Zaghouani, Stephan Vogel, Nizar Habash

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Abstract
The goal of the cognitive machine translation (MT) evaluation approach is to build classifiers which assign post-editing effort scores to new texts. The approach helps estimate fair compensation for post-editors in the translation industry by evaluating the cognitive difficulty of post-editing MT output. The approach counts the number of errors classified in different categories on the basis of how much cognitive effort they require in order to be corrected. In this paper, we present the results of applying an existing cognitive evaluation approach to Modern Standard Arabic (MSA). We provide a comparison of the number of errors and categories of errors in three MSA texts of different MT quality (without any language-specific adaptation), as well as a comparison between MSA texts and texts from three Indo-European languages (Russian, Spanish, and Bulgarian), taken from a previous experiment. The results show how the error distributions change passing from the MSA texts of worse MT quality to MSA texts of better MT quality, as well as a similarity in distinguishing the texts of better MT quality for all four languages.
Anthology ID:
L16-1578
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3644–3651
Language:
URL:
https://aclanthology.org/L16-1578
DOI:
Bibkey:
Cite (ACL):
Irina Temnikova, Wajdi Zaghouani, Stephan Vogel, and Nizar Habash. 2016. Applying the Cognitive Machine Translation Evaluation Approach to Arabic. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3644–3651, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Applying the Cognitive Machine Translation Evaluation Approach to Arabic (Temnikova et al., LREC 2016)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/L16-1578.pdf
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