Editors:
- The first book-length discussion of crucial issues surrounding human and machine translation quality and evaluation
- Contains a comprehensive collection of specially invited papers by leading experts in the field
- Offers insights that are critical to the successful integration of translation technologies in the industry today
Part of the book series: Machine Translation: Technologies and Applications (MATRA, volume 1)
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Table of contents (12 chapters)
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Front Matter
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Scenarios for Translation Quality Assessment
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Front Matter
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Developing Applications of Translation Quality Assessment
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Front Matter
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Translation Quality Assessment in Practice
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Front Matter
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About this book
This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers.
The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.
Reviews
“Translation Quality Assessment: From Principles to Practice offers a broad coverage of a number of approaches to human and machine translation quality assessment (TQA) based on a wide range of practices from research, industry and academia. … this book is a very useful guide for students, researchers and practitioners in the field, including very interesting contributions that can inspire the reader in various directions.” (Emmanouela Patiniotaki, The Journal of Specialised Translation, Issue 32, July, 2019)
“This book is nicely presented with each chapter contributing an important aspect of machine translation quality assessment. The focus of this book is on the product of translation, describing scenarios for translation quality assessment and developing applications of translation quality assessment. … The book embraces dominant methods from different translation scenarios, and provides a comprehensive collection of contributions by international experts in translation quality assessment and human and machine translation evaluation.” (Zhi Huang, The Linguist List, linguistlist.org, February, 2019)
Editors and Affiliations
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ADAPT Centre/School of Applied Language and Intercultural Studies, Dublin City University, Dublin, Ireland
Joss Moorkens
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ADAPT Centre/School of Computing, Dublin City University, Dublin, Ireland
Sheila Castilho, Federico Gaspari
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School of Humanities and Languages, The University of New South Wales, Sydney, Australia
Stephen Doherty
Bibliographic Information
Book Title: Translation Quality Assessment
Book Subtitle: From Principles to Practice
Editors: Joss Moorkens, Sheila Castilho, Federico Gaspari, Stephen Doherty
Series Title: Machine Translation: Technologies and Applications
DOI: https://doi.org/10.1007/978-3-319-91241-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-91240-0Published: 25 July 2018
Softcover ISBN: 978-3-030-08206-2Published: 20 December 2018
eBook ISBN: 978-3-319-91241-7Published: 13 July 2018
Series ISSN: 2522-8021
Series E-ISSN: 2522-803X
Edition Number: 1
Number of Pages: XII, 287
Number of Illustrations: 40 b/w illustrations
Topics: Natural Language Processing (NLP), Computational Linguistics