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E-grāmata: Translation Quality Assessment: From Principles to Practice

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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.  

Recenzijas

I found the reading of this book deeply satisfying in many ways, providing as it did a full overview of cutting-edge research and development in an area that is central to the future of the translation sector. the aim stated in the introduction of helping the reader to continually update knowledge of technology and process in order to maximise [ their] agency as a translator, student, teacher, researcher or process manager is substantially met in the present volume . (Sarah Bawa Mason, Machine Translation, Vol. 33, 2019) 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)

Introduction 1(8)
Joss Moorkens
Sheila Castilho
Federico Gaspari
Stephen Doherty
Part I Scenarios for Translation Quality Assessment
Approaches to Human and Machine Translation Quality Assessment
9(30)
Sheila Castilho
Stephen Doherty
Federieo Gaspari
Joss Moorkens
Translation Quality, Quality Management and Agency: Principles and Practice in the European Union Institutions
39(30)
Joanna Drugan
Ingemar Strandvik
Erkka Vuorinen
Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies
69(26)
Miguel A. Jimenez-Crespo
On Education and Training in Translation Quality Assessment
95(14)
Stephen Doherty
Joss Moorkens
Federico Gaspari
Sheila Castilho
Part II Developing Applications of Translation Quality Assessment
Metrics for Translation Quality Assessment: A Case for Standardising Error Typologies
109(20)
Arle Lommel
Error Classification and Analysis for Machine Translation Quality Assessment
129(30)
Maja Popovic
Quality Expectations of Machine Translation
159(20)
Andy Way
Assessing Quality in Human- and Machine-Generated Subtitles and Captions
179(22)
Stephen Doherty
Jan-Louis Kruger
Part III Translation Quality Assessment in Practice
Machine Translation Quality Estimation: Applications and Future Perspectives
201(36)
Lucia Specia
Kashif Shah
Machine Translation and Self-post-editing for Academic Writing Support: Quality Explorations
237(26)
Sharon O'Brien
Michel Simard
Marie-Josee Goulet
What Level of Quality Can Neural Machine Translation Attain on Literary Text?
263
Antonio Toral
Andy Way