Syntax Based Statistical Machine Translation
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Syntax Based Statistical Machine Translation
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Author : Philip Williams
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2016-08-01
Syntax Based Statistical Machine Translation written by Philip Williams and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-01 with Computers categories.
This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.
Syntax Based Statistical Machine Translation
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Author : Philip Williams
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Syntax Based Statistical Machine Translation written by Philip Williams and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.
Statistical Machine Translation
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Author : Philipp Koehn
language : en
Publisher: Cambridge University Press
Release Date : 2010
Statistical Machine Translation written by Philipp Koehn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
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.
Machine Translation
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Author : Makoto Nagao
language : en
Publisher: Oxford University Press, USA
Release Date : 1989
Machine Translation written by Makoto Nagao and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Computers categories.
A lucid account of the process of machine translation. Nagao (engineering, Kyoto U) details recent developments in MT systems and makes suggestions for their utilization. The book will interest general readers. Annotation copyrighted by Book News, Inc., Portland, OR
Advances In Empirical Translation Studies
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Author : Meng Ji
language : en
Publisher: Cambridge University Press
Release Date : 2019-06-13
Advances In Empirical Translation Studies written by Meng Ji and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with Computers categories.
Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.
Grammatical Inference Algorithms And Applications
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Author : Yasibumi Sakaibara
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-18
Grammatical Inference Algorithms And Applications written by Yasibumi Sakaibara and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-18 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Colloquium on Grammatical Inference, ICGI 2006. The book presents 25 revised full papers and 8 revised short papers together with 2 invited contributions, carefully reviewed and selected. The topics discussed range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to applications to natural language processing.
Decoding Strategies For Syntax Based Statistical Machine Translation
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Author : Fabienne Braune
language : en
Publisher:
Release Date : 2015
Decoding Strategies For Syntax Based Statistical Machine Translation written by Fabienne Braune and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Machine Translation
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Author : Pushpak Bhattacharyya
language : en
Publisher: CRC Press
Release Date : 2015-02-04
Machine Translation written by Pushpak Bhattacharyya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-04 with Business & Economics categories.
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.
Ambient Communications And Computer Systems
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Author : Gregorio Martinez Perez
language : en
Publisher: Springer
Release Date : 2018-03-20
Ambient Communications And Computer Systems written by Gregorio Martinez Perez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-20 with Technology & Engineering categories.
This book includes high-quality, peer-reviewed papers from the International Conference on Recent Advancement in Computer, Communication and Computational Sciences (RACCCS-2017), held at Aryabhatta College of Engineering & Research Center, Ajmer, India on September 2–3, 2017, presenting the latest developments and technical solutions in computational sciences. Data science, data- and knowledge engineering require networking and communication as a backbone and have a wide scope of implementation in engineering sciences. Keeping this ideology in mind, the book offers insights that reflect the advances in these fields from upcoming researchers and leading academicians across the globe. Covering a variety of topics, such as intelligent hardware and software design, advanced communications, intelligent computing technologies, advanced software engineering, the web and informatics, and intelligent image processing, it helps those in the computer industry and academia use the advances of next-generation communication and computational technology to shape real-world applications.
Linguistically Motivated Statistical Machine Translation
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Author : Deyi Xiong
language : en
Publisher: Springer
Release Date : 2015-02-11
Linguistically Motivated Statistical Machine Translation written by Deyi Xiong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-11 with Language Arts & Disciplines categories.
This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.