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Statistical Machine TranslationBy Philipp Koehn

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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.

• Amazon Sales Rank: #1111309 in Books
• Brand: Brand: Cambridge University Press
• Published on: 2010-01-18
• Original language: English
• Number of items: 1
• Dimensions: 9.72" h x .98" w x 6.85" l, 2.25 pounds
• Binding: Hardcover
• 446 pages

• Used Book in Good Condition

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." Robert C. Moore, Microsoft Research"This is an excellent introduction for someone interested in statistical translation. It is quite readable..." Jeffrey Putnam, Computing Reviews

About the Author Philipp Koehn is a lecturer in the School of Informatics at the University of Edinburgh. He is the scientific co-ordinator of the European EuroMatrix project and also involved in research funded by DARPA in the USA. 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.

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Statistical Machine TranslationBy Philipp Koehn PDF

Statistical Machine TranslationBy Philipp Koehn PDF