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Statistical Machine Translation
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.
Neural Machine Translation
Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.
Neural Machine Translation
Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.
Syntax-based Statistical Machine Translation
This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also descri...
Learning Machine Translation
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Neural Representations of Natural Language
This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas – as Webster’s 1923 “English Composition and Literature” puts it: “A sentence is a group of words expressing a complete thought”. Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other “smart” systems currently being developed. Providing an overview of the research in the area, from Bengio et al.’s seminal work on a “Neural Probabilistic Language Model” in 20...
Advances in Empirical Translation Studies
Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.
A Tomb With a View – The Stories & Glories of Graveyards
A FINANCIAL TIMES, I PAPER AND STYLIST BOOK OF THE YEAR 'In his absorbing book about the lost and the gone, Peter Ross takes us from Flanders Fields to Milltown to Kensal Green, to melancholy islands and surprisingly lively ossuaries . . . a considered and moving book on the timely subject of how the dead are remembered, and how they go on working below the surface of our lives.' - Hilary Mantel 'Ross is a wonderfully evocative writer, deftly capturing a sense of place and history, while bringing a deep humanity to his subject. He has written a delightful book.' - The Guardian 'The pages burst with life and anecdote while also examining our relationship with remembrance.' - Financial Times (...
Choosing Your Religion
Choosing your Religion is a guide to Christian denominations in the U.S. It describes, in concise form, the distinct features, beliefs, practices, and origins of 18 faiths, most of which are fixtures in nearly every American town and city. While these churches are familiar to all, their differences are not commonly understood. An ideal resource for those re-evaluating, or considering church for the first time, the Book of Denominations allows readers to easily acquire the broadest possible view of the Christian religion by examining its many facets, its different denominations. It may also serve current churchgoers looking to learn more about their own faith. The book contains a wealth of information organized for the benefit of the inquiring reader. For each faith group presented, it answers questions such as: What do they believe? How did it start? How many people belong? How do they worship? The book also includes an overview of the Christian religion and a glossary of religious terms.
Translation in Transition
Extraordinary advances in machine translation over the last three quarters of a century have profoundly affected many aspects of the translation profession. The widespread integration of adaptive “artificially intelligent” technologies has radically changed the way many translators think and work. In turn, groundbreaking empirical research has yielded new perspectives on the cognitive basis of the human translation process. Translation is in the throes of radical transition on both professional and academic levels. The game-changing introduction of neural machine translation engines almost a decade ago accelerated these transitions. This volume takes stock of the depth and breadth of resulting developments, highlighting the emerging rivalry of human and machine intelligence. The gathering and analysis of big data is a common thread that has given access to new insights in widely divergent areas, from literary translation to movie subtitling to consecutive interpreting to development of flexible and powerful new cognitive models of translation.
