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.

At a time when information technology has become a regular tool of specialised translators in all aspects of their work, it is useful to place the activity of technical translation into its appropriate environment and to describe it from the point of view of its role in the broader context of communication in which it occurs. The advent of automated alternatives to human translation has fundamentally affected the profession, its products and the relationship between translators and their clients.This book presents and discusses the process of translation against this background. The context in which translation is normally studied is widened in order to re-examine the process of translation as part of interlingual text production and to analyse the manner in which the new tools affect the product of translation.This book is of particular relevance in modern translator training courses. Contents 1. The language industry and translation, 2. Aspects of language, 3. Elements of communication theory, 4. A theory of text types and messages, 5. The nature of translation, 6. Specifications: Factors influencing the translation, 7. Preparation for translation, 8. Steps in translation, 9. Human and Machine Translation, 10 Pragmatic circumstances of automation, 11. Translation in an information technology environment. Bibliography + Index.

The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.

Automatic Translation of Languages is a collection of papers that discusses the various concerns in automatic language translation systems. The text first covers algebraic linguistics and machine translation, and then proceeds to tackling the main concepts in automatic translation of languages. Next, the selection deals with the equivalence of models of language used in the fields of mechanical translation and information retrieval. The text also discusses computational procedure in linguistic research. The next chapters detail syntax and syntactic integration. The book will be of great use to scientists and professionals who involved in the research and development of computerized language translation systems.

This dictionary is intended for anyone who is interested in translation and translation technology. Especially, translation as an academic discipline, a language activity, a specialized profession, or a business undertaking. The book covers theory and practice of translation and interpretation in a number of areas. Addressing and explaining important concepts in computer translation, computer-aided translation, and translation tools. Most popular and commercially available translation software are included along with their website addresses for handy reference. This dictionary has 1,377 entries. The entries are alphabetized and defined in a simple and concise manner.

This one-volume Encyclopedia covers both the conceptual framework and history of translation. Organised alphabetically for ease of access, a team of experts from around the world has been gathered together to provide unique, new insights.

Automating Linguistics offers an in-depth study of the history of the mathematisation and automation of the sciences of language. In the wake of the first mathematisation of the 1930s, two waves followed: machine translation in the 1950s and the development of computational linguistics and natural language processing in the 1960s. These waves were pivotal given the work of large computerised corpora in the 1990s and the unprecedented technological development of computers and software.Early machine translation was devised as a war technology originating in the sciences of war, amidst the amalgamate of mathematics, physics, logics, neurosciences, acoustics, and emerging sciences such as cybernetics and information theory. Machine translation was intended to provide mass translations for strategic purposes during the Cold War. Linguistics, in turn, did not belong to the sciences of war, and played a minor role in the pioneering projects of machine translation.Comparing the two trends, the present book reveals how the sciences of language gradually integrated the technologies of computing and software, resulting in the second-wave mathematisation of the study of language, which may be called mathematisation-automation. The integration took on various shapes contingent upon cultural and linguistic traditions (USA, ex-USSR, Great Britain and France). By contrast, working with large corpora in the 1990s, though enabled by unprecedented development of computing and software, was primarily a continuation of traditional approaches in the sciences of language sciences, such as the study of spoken and written texts, lexicography, and statistical studies of vocabulary.