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Statistical Machine Translation

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This introductory text to statistical machine translation (SMT) provides all of the theories and methods needed to build a statistical machine translator, such as Google Language Tools and Babelfish. In general, statistical techniques allow automatic translation systems to be built quickly for any language-pair using only translated texts and generic software. With increasing globalization, statistical machine translation will be central to communication and commerce. Based on courses and tutorials, and classroom-tested globally, it is ideal for instruction or self-study, for advanced undergraduates and graduate students in computer science and/or computational linguistics, and researchers in natural language processing. The companion website provides open-source corpora and tool-kits.

Hardcover: 446 pages

Publisher: Cambridge University Press; 1 edition (January 18, 2010)

Language: English

ISBN-10: 0521874157

ISBN-13: 978-0521874151

Product Dimensions: 6.8 x 1 x 9.7 inches

Shipping Weight: 2.4 pounds (View shipping rates and policies)

Average Customer Review: 4.6 out of 5 stars  See all reviews (5 customer reviews)

Best Sellers Rank: #703,000 in Books (See Top 100 in Books) #65 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Natural Language Processing #9429 in Books > Textbooks > Computer Science #169802 in Books > Reference

Philipp Koehn is a superb lecturer and teacher in the area of statistical machine translation (SMT). I have being living off his lecture notes from the ACL, LSA summer session and Edinburgh for years and eagerly waiting for this book to tie everything together.Koehn has the ability to take complex statistical concepts and make them comprehensible. And he has an encyclopedic knowledge of the state-of-the-art in SMT. His bibliography alone is worth the price of this book.This book will be the gold standard in SMT for years to come. I would highly recommend to students and professionals in the field.

I currently work at NLP software company in South Korea as an NLU software developer.When I bought this book, I was finishing my own MT decoder and starting tobuild a rudimentary IBM word alignment model trainer.This book greatly contributed to the project in that it deeply corrected my wrong understanding ofmany concepts such as dynamic programming, optimization, beam search, and etc.Best part : It includes easy-to-understand pseudo-code for IBM 1~5 word alignment process.It was also helpful in improving the performance of existing decoder.As one of the leading figures in well-known Moses project and Euro Matrix,author's explanation is firmly grounded upon practical experience andincludes a lot of elements required for building a prototype MT system.I believe reading this book with the background knowledgethat you can learn in such books as Artificial Intelligence: A Modern Approach or Mitchell's Machine Learning,may maximize your learning rate, since the subject stuffs inthese books are highly inter-related with each others,for example, unsupervised learning algorithm(especially EM),optimization and search.This book is top-ranked in NLP category of my personal book shelf.I guess you won't regret if you purchase one.

It is more or less obligatory reading for anyone working on the topic. Goes through most important methods and approaches to implementing the system and the algorithms are described well enough that one can re-implement them easily. There are some errors that can be problematic if you forget to check the errata. Sometimes the notations of formulas are a bit hard to follow. All in all rather well written school-book for contemporary statistical machine translation.

well written and entertaining text book. would have liked more on hierarchical parsing models. the kindle edition was great except that the diagrams could not be zoomed

Excellent Book in English wIth brain neutral explanation. Not too much alien symbols. Great thanx to the author. Really good book.!

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