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MACHINE TRANSLATION BY PUSHPAK

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MACHINE TRANSLATION BY PUSHPAK BHATTACHARYYA

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It can be one of your early morning readings Machine Translation By Pushpak Bhattacharyya This is a soft file book that can be survived downloading from on the internet book. As known, in this advanced age, technology will certainly alleviate you in doing some activities. Also it is merely checking out the visibility of publication soft documents of Machine Translation By Pushpak Bhattacharyya can be additional attribute to open up. It is not just to open as well as save in the gizmo. This time in the morning and various other free time are to check out guide Machine Translation By Pushpak Bhattacharyya

Review

"…a clear, well-written introduction to a key area in computer science." ?Ernest Davis, in Computing Reviews

About the Author

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MACHINE TRANSLATION BY PUSHPAK BHATTACHARYYA

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Three paradigms have dominated machine translation (MT)?rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). These paradigms differ in the way they handle the three fundamental processes in MT?analysis, transfer, and generation (ATG). In its pure form, RBMT uses rules, while SMT uses data. EBMT tries a combination?data supplies translation parts that rules recombine to produce translation.

Machine Translation compares and contrasts the salient principles and practices of RBMT, SMT, and EBMT. Offering an exposition of language phenomena followed by modeling and experimentation, the text:

Introduces MT against the backdrop of language divergence and the Vauquois triangle

Presents expectation maximization (EM)-based word alignment as a turning point in the history of MT

Discusses the most important element of SMT?bilingual word alignment from pairs of parallel translations

Explores the IBM models of MT, explaining how to find the best alignment given a translation pair and

how to find the best translation given a new input sentence

Covers the mathematics of phrase-based SMT, phrase-based decoding, and the Moses SMT environment

Provides complete walk-throughs of the working of interlingua-based and transfer-based RBMT

Analyzes EBMT, showing how translation parts can be extracted and recombined to translate a new input,

all automatically

Includes numerous examples that illustrate universal translation phenomena through the usage of specific

languages

Machine Translation is designed for advanced undergraduate-level and graduate-level courses in machine translation and natural language processing. The book also makes a handy professional reference for computer engineers.

Dimensions: 9.30" h x .80" w x 6.20" l, .0 pounds

"…a clear, well-written introduction to a key area in computer science." ?Ernest Davis, in Computing Reviews

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Information Processing and vice president-elect of Association of Computational Linguistics (ACL).

Most helpful customer reviews

0 of 1 people found the following review helpful. Four Stars

By Adedayo Ominiyi Excellent book. A must read

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MACHINE TRANSLATION BY PUSHPAK BHATTACHARYYA

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Review

"…a clear, well-written introduction to a key area in computer science." ?Ernest Davis, in Computing Reviews

About the Author

Pushpak Bhattacharyya is Vijay and Sita Vashee chair professor of computer science and engineering at the Indian Institute of Technology (IIT) Bombay, where he has been teaching and researching for the last 25 years. He was educated at IIT Kharagpur (B.Tech), IIT Kanpur (M.Tech), and IIT Bombay (Ph.D). While earning his Ph.D, he was visiting scholar at the Massachusetts Institute of Technology. Subsequently, he has been visiting professor at Stanford University and University of Grenoble, and distinguished lecturer at the University of Houston. Dr. Bhattacharyya’s research interests include natural language processing, machine learning, machine translation, information extraction, sentiment analysis, and cross-lingual search, in which he has published extensively. Currently, he is associate editor of ACM Transactions on Asian Language Information Processing and vice president-elect of Association of Computational Linguistics (ACL).

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