Machine Translation
Autor Pushpak Bhattacharyyaen Limba Engleză Paperback – 13 ian 2015
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
Print Versions of this book also include access to the ebook version.
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Specificații
ISBN-13: 9781439897188
ISBN-10: 1439897182
Pagini: 264
Ilustrații: 46 black & white illustrations, 58 black & white tables
Dimensiuni: 156 x 234 x 20 mm
Greutate: 0.57 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 1439897182
Pagini: 264
Ilustrații: 46 black & white illustrations, 58 black & white tables
Dimensiuni: 156 x 234 x 20 mm
Greutate: 0.57 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Cuprins
Introduction. Learning Bilingual Word Mappings. IBM Model of Alignment. Phrase-Based Machine Translation. Rule-Based Machine Translation. Example-Based Machine Translation.
Notă biografică
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).
Recenzii
"…a clear, well-written introduction to a key area in computer science."
—Ernest Davis, in Computing Reviews
—Ernest Davis, in Computing Reviews
Descriere
This book compares and contrasts the principles and practices of rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). Presenting numerous examples, the text introduces language divergence as the fundamental challenge to machine translation, emphasizes and works out word alignment, explores IBM models of machine translation, covers the mathematics of phrase-based SMT, provides complete walk-throughs of the working of interlingua-based and transfer-based RBMT, and analyzes EBMT, showing how translation parts can be extracted and recombined to automatically translate a new input.