Joss Moorkens, Séamus Lankford, Andy Way

418.020285

23

Trade Paperback

1032436808

9781032436807

Yes

College Audience

9.2 in

17.8 Oz

6.1 in

P308.M65 2025

2024-015547

English

248 Pages

Automating Translation

2024

Taylor & Francis Group

This is an indispensable textbook for any translation students and professionals working in the translation industry who want to learn about the recent developments in the field of machine translation. Written in a clear and engaging style, it accommodates readers of all levels, benefiting from the authors' extensive experience in the field. Its comprehensive scope and insightful perspective make this book an invaluable resource for anyone who wants to learn about the modern machine translation approaches. Readers without a computational background but who want to learn more about how machine translation works will appreciate the technical details provided in text boxes and extra reading materials. I will definitely recommend this book to my students. - Professor Constantin Orasan, University of Surrey Tailored for translation students and language professionals, this textbook offers a comprehensive and accessible exploration of all aspects of machine translation. From data and the inner workings of MT to evaluation and the customisation of your own LLM, every topic is covered. With its clear explanations, valuable pointers to open-source tools and recommended additional readings, this book empowers readers to engage in informed discussions about the appropriate use of MT. - Professor Lieve Macken, Ghent University, Belgium

Routledge Introductions to Translation and Interpreting Ser.

Translating & Interpreting, Linguistics / General

Language Arts & Disciplines

Translation technology is essential for translation students, practising translators, and those working as part of the language services industry, but looming above others are the tools for automating translation: machine translation and, more recently, Generative AI based on Large Language Models (LLMs). This book, authored by leading experts, demystifies machine translation, explaining its origins, its training data, how neural machine translation and LLMs work, how to measure their quality, how translators interact with contemporary systems for automating translation, and how readers can build their own machine translation or LLM. In later chapters, the scope of the book expands to look more broadly at translation automation in audiovisual translation and localisation. Importantly, the book also examines the sociotechnical context, focusing on ethics and sustainability. Enhanced with activities, further reading and resource links, including online support material on the Routledge Translation studies portal, this is an essential textbook for students of translation studies, trainee and practising translators and users of MT and multilingual LLMs., Translation technology is essential for translation students, practising translators, and those working as part of the language services industry, but looming above others are the tools for automating translation: machine translation and, more recently, generative AI based on large language models (LLMs). This book, authored by leading experts, demystifies machine translation, explaining its origins, its training data, how neural machine translation and LLMs work, how to measure their quality, how translators interact with contemporary systems for automating translation, and how readers can build their own machine translation or LLM. In later chapters, the scope of the book expands to look more broadly at translation automation in audiovisual translation and localisation. Importantly, the book also examines the sociotechnical context, focusing on ethics and sustainability. Enhanced with activities, further reading and resource links, including online support material on the Routledge Translation studies portal, this is an essential textbook for students of translation studies, trainee and practising translators, and users of MT and multilingual LLMs., This book, authored by leading experts, demystifies machine translation, explaining its origins, its training data, how neural machine translation and LLMs work, how to measure their quality, how translators interact with contemporary systems for automating translation, and how readers can build their own machine translation or LLM.

Contents Series Editor's Foreword Preface Abbreviations and Acronyms Chapter 1 - The Roots of Machine Translation Chapter 2 - Data for Machine Translation Chapter 3 - Translation Memory and Computer-Assisted Translation tools Chapter 4 - Neural Networks and Neural Machine Translation Chapter 5 - Machine Translation Evaluation Chapter 6 - Neural Machine Translation: Build or Buy? Chapter 7 - Building Machine Translation Models with Colab Chapter 8 - Machine Translation Post-Editing Chapter 9 - Machine Translation in Multimedia Translation and Localisation Chapter 10 - Large Language Models and Multilingual Language Models: The Future of Machine Translation? Chapter 11 - Sociotechnical Effects of Machine Translation Afterword Glossary

Textbook

Taylor & Francis Group

9781032436807