In:Multiword Units in Machine Translation and Translation Technology
Edited by Ruslan Mitkov, Johanna Monti, Gloria Corpas Pastor and Violeta Seretan
[Current Issues in Linguistic Theory 341] 2018
► pp. 61–80
How do students cope with machine translation output of multiword units? An exploratory study
Published online: 20 July 2018
https://doi.org/10.1075/cilt.341.03dae
https://doi.org/10.1075/cilt.341.03dae
Abstract
In this chapter, we take a closer look at students’ post-editing of multiword units (MWUs) from English into Dutch. The
data consists of newspaper articles post-edited by translation students as collected by means of advanced keystroke
logging tools.
We discuss the quality of the machine translation (MT) output for various types of MWUs, and compare this with the
final post-edited quality. In addition, we examine the external resources consulted for each type of MWU. Results
indicate that contrastive MWUs are harder to translate for the MT system, and harder to correct by the student
post-editors than non-contrastive MWUs. We further find that consulting a variety of external resources helps student
post-editors solve MT problems.
Article outline
- 1.Introduction
- 2.Experimental set-up
- 3.Analysis
- 4.Conclusion
- 5.Future work
Notes References
References (8)
Alabau, V. Bonk, R., Buck, C., Carl, M., Casacuberta, F., Martínez, M., González, J., Koehn, P., Leiva, L., Mesa-Lao, B., Ortiz, D., Saint-Amand, H., Sanchis, G., & Tsoukala, C. (2013). CASMACAT: An Open Source Workbench for Advanced Computer Aided Translation. The Prague Bulletin of Mathematical Linguistics, 100, 101–112. doi:.
Daems, J., Macken, L., & Vandepitte, S. (2013). Quality as the sum of its parts: A two-step approach for the identification of translation problems
and translation quality assessment for HT and MT + PE. In Proceedings of the MT Summit XIV Workshop on Post-editing Technology and Practice, 63–71.
Daems, Joke, Vandepitte, S., Hartsuiker, R., & Macken, L. (2017). Translation methods and experience : a comparative analysis of human translation and post-editing
with students and professional translators. META, 62(2), 245–270.
Göpferich, S. (2010). The translation of instructive texts from a cognitive perspective. In F. Alves, S. Göpferich, & I. Mees (Eds.) New approaches in Translation Process Research (pp.5–65). Frederiksberg: Samfundslitteratur.
Koehn, P., & Germann, U. (2014). The impact of machine translation quality on humanpost-editing. In Proceedings of the EACL 2014 Workshop on Humans and Computer-assisted Translation, 38–46, Gothenburg,Sweden. Association for Computational Linguistics.
Leijten, M., & Van Waes, L. (2013). Keystroke Logging in Writing Research: Using Inputlog to Analyse and Visualize Writing
Processes. Written Communication. 30(3), 358–392. doi:
Mendoza Rivera, O., Mitkov, R., & Corpas Pastor, G. (2013). A flexible framework for collocation retrieval and translation from parallel and comparable
corpora. In Proceedings of the Workshop on Multi-word Units in Machine Translation and Translation Technology, 18–25, Nice.
Monti, J., Barreiro A., Elia A., Marano F., & Napoli A. (2011). Taking on new challenges in multi-word unit processing for Machine Translation. In F. Sanchez-Martinez, J. A. Perez-Ortiz (Eds.) Proceedings of the Second International Workshop on Free/Open-Source Rule-Based Machine
Translation, 11–19, Barcelona, Spain.
