Abstract
Translated texts, in any language, have unique characteristics that set them apart from texts originally written in the same language. Translation studies is a research field that focuses on investigating these characteristics. Until recently, research in computational linguistics, and specifically in machine translation, has been entirely divorced from translation studies. The main goal of this tutorial is to introduce some of the findings of translation studies to researchers interested mainly in machine translation, and to demonstrate that awareness of these findings can result in better, more accurate machine translation systems (This chapter synthesizes material that has been previously published by the author and colleagues, in particular in Volansky et al. (2015); Rabinovich and Wintner (2015); Lembersky et al. (2011, 2012a, b, 2013); and Twitto et al. (2015)).
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- 1.
We use ‘originals’ here as opposed to ‘translations’, although translation are of course also originally created by translators.
- 2.
We use “domain” rather freely henceforth to indicate not only the topic of a corpus but also its modality (written vs. spoken), register, genre, date, etc.
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Acknowledgements
I am grateful to Noam Ordan for his immense help with the research reported here. Thanks are due to all my other collaborators on these works, including Gennadi Lembersky, Vered Volansky, Udi Avner, Naama Twitto and Ella Rabinovich. Special thanks are due to Agata Savary, not least for her continuous encouragement. I am grateful to the three anonymous reviewers whose constructive comments greatly improved the quality of the presentation. This research was supported by a grant from the Israeli Ministry of Science and Technology.
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Wintner, S. (2017). Computational Approaches to Translation Studies. In: Marcel, P., Zimányi, E. (eds) Business Intelligence. eBISS 2016. Lecture Notes in Business Information Processing, vol 280. Springer, Cham. https://doi.org/10.1007/978-3-319-61164-8_2
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