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.
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'Philipp Koehn has provided the first comprehensive text for the rapidly growing field of statistical machine translation. This book is an invaluable resource for students, researchers, and software developers, providing a lucid and detailed presentation of all the important ideas needed to understand or create a state-of-the-art statistical machine translation system.' Robert C. Moore, Principal Researcher, Microsoft Research
'The book primarily represents an ideal introduction to the field of statistical machine translation, but also tackles many of the recent results in this area. It is the product of the many years of both active research and extensive teaching of the author … Each chapter is additionally endowed with a summary, further reading and exercises, achieving thus completely the proposed goal of an accessible introduction to the statistical machine translation field. Apart from its formative role for beginners, the book also stands as a complete guide for researchers in a domain of high interest and rapid expansion … For all these reasons, this book should be welcomed as a highly valuable publication.' Zentralblatt MATH
'The book primarily represents an ideal introduction to the field of statistical machine translation, but also tackles many of the recent results in this area. It is the product of the many years of both active research and extensive teaching of the author … Each chapter is additionally endowed with a summary, further reading and exercises, achieving thus completely the proposed goal of an accessible introduction to the statistical machine translation field. Apart from its formative role for beginners, the book also stands as a complete guide for researchers in a domain of high interest and rapid expansion … For all these reasons, this book should be welcomed as a highly valuable publication.' Zentralblatt MATH
Book Description
Automatic language translation systems like those used by Google, have been revolutionized by recent advances in the methods used in statistical machine translation. This first textbook on the topic explains these innovations carefully and shows the reader, whether a student or a developer, how to build their own translation system.
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9 of 9 people found the following review helpful
5.0 out of 5 stars
Gold Standard in SMT
27 Jan 2010
By Jay Yamada
- Published on Amazon.com
Format:Hardcover|Amazon Verified Purchase
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.
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.
3 of 3 people found the following review helpful
5.0 out of 5 stars
Must-Have Item for MT System Developer
30 Sep 2010
By Sunghyun Kim
- Published on Amazon.com
Format:Hardcover|Amazon Verified Purchase
I currently work at NLP software company in South Korea as MT system developer.
When I purchased this book, I was finishing my own MT decoder and starting to
build IBM word alignment model trainer. This book greatly contributed to the project
in that it deeply corrected my wrong understanding of heuristic search, and more than
any thing else, included easy-to-understand pseudo-code for word alignment process.
It was also helpful for improving performance of existing decoder.
As one of the leading figures in well-known Moses project, author's explanation is firmly
grounded upon practical experience and includes a lot of elements required for building a prototype MT system.
I believe reading this book with the background knowledge that can be gained
from such book as Artificial Intelligence : A Modern Approach or Mitchell's Machine Learning, may
maximize your learning rate, since the subject stuffs in these 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.
When I purchased this book, I was finishing my own MT decoder and starting to
build IBM word alignment model trainer. This book greatly contributed to the project
in that it deeply corrected my wrong understanding of heuristic search, and more than
any thing else, included easy-to-understand pseudo-code for word alignment process.
It was also helpful for improving performance of existing decoder.
As one of the leading figures in well-known Moses project, author's explanation is firmly
grounded upon practical experience and includes a lot of elements required for building a prototype MT system.
I believe reading this book with the background knowledge that can be gained
from such book as Artificial Intelligence : A Modern Approach or Mitchell's Machine Learning, may
maximize your learning rate, since the subject stuffs in these 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.
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