Editorial Reviews. Review. "Philipp Koehn has provided the first comprehensive text for this rapidly growing field of statistical machine translation. This book is. La 4e de couverture indique: "The field of machine translation has recently been energized by the emergence of statistical techniques, which have brought the. Statistical Machine Translation provides a comprehensive and clear book is aimed at students or researchers interested in a thorough entry-point to the.
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Book: "Statistical Machine Translation". Philipp Koehn Hardcover, pages. Publisher: Cambridge University Press ISBN ISBN Core - Artificial Intelligence and Natural Language Processing - Statistical Machine Translation - by Philipp Koehn. Export citation; download the print book. "Philipp Koehn has provided the first comprehensive text for this rapidly growing field of statistical machine translation. This book is an invaluable resource for.
He has also collaborated with leading companies in the field, such as Systran and Asia Online. He implemented the widely used decoder Pharoah, and is leading the development of the open source machine translation toolkit Moses. Statistical Machine Translation. Philipp Koehn. La 4e de couverture indique: This class-tested textbook, authored by an active researcher in the field, provides a gentle and accessible introduction to the latest methods and enables the reader to build machine translation systems for any language pair.
Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation. Read more Read less. Kindle Cloud Reader Read instantly in your browser. Customers who bought this item also bought. Page 1 of 1 Start over Page 1 of 1. Yoav Goldberg. Ian Goodfellow.
Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library. Natural Language Processing with PyTorch: Delip Rao. Speech and Language Processing 2-Download. Editorial Reviews Review "Philipp Koehn has provided the first comprehensive text for this rapidly growing field of statistical machine translation. This book is an invaluable resource for students, researcher, 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.
Moore, Microsoft Research "This is an excellent introduction for someone interested in statistical translation. It is quite readable This class-tested text establishes background in NLP and statistics, then develops the basics through to current research. By the end readers can build their own translation systems.
For advanced undergraduates in computer science, graduate students in computer science and computational linguistics, and researchers in NLP; for instruction or self-study. See all Editorial Reviews. Product details File Size: Up to 4 simultaneous devices, per publisher limits Publisher: December 17, Sold by: English ASIN: Enabled X-Ray: Not Enabled. Share your thoughts with other customers. Write a customer review. Showing of 5 reviews. Top Reviews Most recent Top Reviews. There was a problem filtering reviews right now.
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Hardcover Verified download. This book greatly contributed to the project in that it deeply corrected my wrong understanding of many concepts such as dynamic programming, optimization, beam search, and etc. Best part: 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 and includes a lot of elements required for building a prototype MT system. I believe reading this book with the background knowledge that 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 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 download one. 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. Kindle Edition Verified download. 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. First, there are millions of possible combinations.
The possibilities, needless to say, multiply out.
Second, and at least as seriously, the English words will often be in a different order from the French words, so you need to take account of that in some way; here, the basic solution is for the translation algorithm to impose a penalty for changing the order, with big changes costing more than small ones.
But surely there must be more to translation than just looking things up in huge tables and picking the highest-scoring combo?
Indeed there is: the fact of the matter, however, is that, with our present level of understanding, this is the method that works best. At the end of the book, there is a chapter briefly describing smarter methods that pay some attention to grammar; but they're not that much smarter, they're much more challenging to implement, and the gains are modest.
When you don't really understand planetary motion, you use the best model you can come up with and try to make it fit the data as well as you can. It is hard to believe that the ancient Greek astronomers really thought that the planets moved on invisible crystal spheres attached to other invisible crystal spheres, but you can make it work quite well as a predictive theory if you're prepared to do the necessary number-crunching.
As Laplace says, this turned out to be a far more fruitful research direction than imaginative armchair theorizing. People developed the system of equants, deferents and epicycles as far as it would go, and, by carefully studying what went wrong, they eventually found something that was genuinely better.
In Machine Translation, we haven't yet reached the Newtonian stage. But if you want to know the details of how those crystal spheres work, Koehn's book is the one to download. Go to Google Translate and try translating the two sentences "I saw few people" and "I saw a few people" into various languages.
In some cases, the results will, as you'd expect, be different; in others, they'll be the same.