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Machine Translation

, Volume 33, Issue 3, pp 259–268 | Cite as

Chan Sin-Wai (ed): The human factor in machine translation

Routledge Studies in Translation Technology, Routledge, 1st edition (2018), xii+256pp, ISBN 781-13-855-1213 (Hardback), 978-13-151-4753-6 (e-book)
  • Sheila CastilhoEmail author
Book review

Summary

This book “The Human Factors in Machine Translation” edited by Chan Sin-Wai—also the series editor of Studies in Translation Technology—brings together twelve chapters covering a variety of topics such as localisation, terminology and crowdsourcing. The goal of the book is to give a comprehensive look at the role of the human translator in machine translation (MT).

The book is not divided into particular parts, which makes it difficult at times to understand where the narrative is leading the reader. As the chapters do not follow any specific order either, the contents of this book are perhaps best served as reference chapters depending on the reader’s specific needs. The main draw of the book is the human factor in its title, and so I was eager to see how the human factor was dealt in each chapter for each topic. Accordingly, this review focuses on what the title promises to address: the human factor in MT.

Introduction (Chan Sin-Wai)

The Introduction provides a summary of...

Notes

References

  1. Bowker L (2015) Translatability and user eXperience: compatible or inconflict? Localisation Focus-Int J Localisation 14(2):13–27Google Scholar
  2. Passban P, Way A, Liu Q (2015) Benchmarking SMT performance for Farsi using the TEP++ corpus. In: Proceedings of the 18th annual conference of the European association for machine translation, Antalya, pp 82–88Google Scholar
  3. Toral A, Way A (2015a) Machine-assisted translation of literary text: a case study. Transl Spaces 4:241–268CrossRefGoogle Scholar
  4. Toral A, Way A (2018) What level of quality can neural machine translation attain on literary text? In: Moorkens J, Castilho S, Gaspari F, Doherty S (eds) translation quality assessment: from principles to practice. Springer, New York, pp 263–287CrossRefGoogle Scholar
  5. Toral A, Way A (2015b) Translating literary text between related languages using SMT. In: Proceedings of the fourth workshop on computational linguistics for literature, Denver, pp 123–132Google Scholar
  6. Voigt R, Jurafsky D (2012) Towards a literary machine translation: the role of referential cohesion. In: Workshop on computational linguistics for literature, Montreal, Canada, pp 18–25Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.ADAPT Centre, School of ComputingDublin City UniversityDublinIreland

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