Statistical Machine Translation Philipp Koehn (University of Edinburgh) Cambridge University Press, 2010, xii+433 pp; ISBN 978 0 521 87415 1, $60.00
Statistical Machine Translation provides a comprehensive and clear introduction to the most prominent techniques employed in the field of the same name (SMT) This textbook is aimed at students or researchers interested in a thorough entry point to the field, and it does an excellent job of providing basic understanding for each of the many pieces of a statistical translation system. I consider this book to be an essential addition to any advanced undergraduate course or graduate course on SMT. The book is divided into three parts: Foundations, Core Methods, and Advanced Topics. Foundations (75 pages) covers an introduction to translation, working with text, and probability theory. Core Methods (170 pages) covers the main components of a standard phrase based SMT system. Advanced Topics (125 pages) covers discriminative training and linguistics in SMT, including an in depth discussion of syntactic SMT. The text as a whole assumes a certain familiarity with natural language processing; though the Foundations section provides an effort to fill in the gaps, the book's focus is decidedly translation. As such, students unfamiliar with NLP may sometimes need to consult a general NLP text. The book aims to provide a thorough introduction to each component of a statistical translation system, and it definitely succeeds in doing so. Supplementing this core material for each chapter is a highly inclusive Further Reading section. These sections provide brief narratives highlighting many relevant papers and alternative techniques for each topic addressed in the chapter. I suspect many readers will find these literature pointers to be quite valuable, from students wishing to dive deeper, to experienced SMT researchers wishing to get started in a new sub field. Each chapter also closes with a short list of exercises. Many of these are very challenging (accurately indicated by a star rating system) and involve getting your hands dirty with tools downloaded from the Web. The usefulness of these exercises will depend largely on the instructor's tastes; I view them as a bonus rather than a core feature of the book.
Computational Linguistics