• ISBN13: 9781032323800
• Binding: Paperback
• Subject: Computer Science and Information Technology
• Publisher: Taylor & Francis Group
• Publisher Imprint: N/A
• Publication Date: November 10, 2023
• Pages: 218
• Original Price: GBP 35.99
• Language: English
• Edition: 1
• Item Weight: 310 grams
• BISAC Subject(s): Data Science / Machine Learning

Machine Learning in Translation introduces machine learning (ML) theories and technologies relevant to translation, with a focus on how these technologies serve humans. The book explores the overlap between human and machine learning in translation, helping linguists, translators, and localizers identify their unique value in an ML-driven environment. It covers key ML tasks in translation, including machine translation, quality assessment, and Natural Language Processing (NLP). The book emphasizes the importance of data management, proposing that translators' value lies in their ability to create and leverage language data. It also highlights the need for new knowledge in traditional translation education and advocates for a human-centred approach to ML. Ideal for students and professionals in translation, localisation, and language technology.

Peng Wang is a freelance conference interpreter with the Translation Bureau, Public Works and Government Services Canada, a part-time professor in the School of Translation and Interpretation, University of Ottawa and Course designer and instructor for Think NLP and Machine Translation Masterclass at the Localization Institute. She has published two books in Chinese, including Harry Potter and Its Chinese Translation.

David B. Sawyer is Director of Language Testing at the U.S. State Department's Foreign Service Institute and a Senior Lecturer at the University of Maryland, USA. He is the author of Foundations of Interpreter Education: Curriculum and Assessment and co-editor of The Evolving Curriculum in Interpreter and Translator Education: Stakeholder Perspectives and Voices (both John Benjamins).