Syntax-based Statistical Machine Translation

Syntax-based Statistical Machine Translation

Author: Philip Williams

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 190

ISBN-13: 3031021649

DOWNLOAD EBOOK

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.


Book Synopsis Syntax-based Statistical Machine Translation by : Philip Williams

Download or read book Syntax-based Statistical Machine Translation written by Philip Williams and published by Springer Nature. This book was released on 2022-05-31 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Syntax-based Statistical Machine Translation

Author: Philip Williams

Publisher: Morgan & Claypool Publishers

Published: 2016-08-01

Total Pages: 211

ISBN-13: 1627055029

DOWNLOAD EBOOK

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.


Book Synopsis Syntax-based Statistical Machine Translation by : Philip Williams

Download or read book Syntax-based Statistical Machine Translation written by Philip Williams and published by Morgan & Claypool Publishers. This book was released on 2016-08-01 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Syntax-based Statistical Machine Translation

Author: Philip Williams

Publisher: Springer

Published: 2016-08-11

Total Pages: 190

ISBN-13: 9783031010361

DOWNLOAD EBOOK

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.


Book Synopsis Syntax-based Statistical Machine Translation by : Philip Williams

Download or read book Syntax-based Statistical Machine Translation written by Philip Williams and published by Springer. This book was released on 2016-08-11 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Linguistically Motivated Statistical Machine Translation

Linguistically Motivated Statistical Machine Translation

Author: Deyi Xiong

Publisher: Springer

Published: 2015-02-11

Total Pages: 159

ISBN-13: 9812873562

DOWNLOAD EBOOK

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.


Book Synopsis Linguistically Motivated Statistical Machine Translation by : Deyi Xiong

Download or read book Linguistically Motivated Statistical Machine Translation written by Deyi Xiong and published by Springer. This book was released on 2015-02-11 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Machine Translation

Statistical Machine Translation

Author: Philipp Koehn

Publisher: Cambridge University Press

Published: 2010

Total Pages: 447

ISBN-13: 0521874157

DOWNLOAD EBOOK

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.


Book Synopsis Statistical Machine Translation by : Philipp Koehn

Download or read book Statistical Machine Translation written by Philipp Koehn and published by Cambridge University Press. This book was released on 2010 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

KI 2002: Advances in Artificial Intelligence

KI 2002: Advances in Artificial Intelligence

Author: Matthias Jarke

Publisher: Springer Science & Business Media

Published: 2002-09-04

Total Pages: 319

ISBN-13: 3540441859

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 25th Annual German conference on Artificial Intelligence, KI 2002, held in Aachen, Germany in September 2002. The 20 revised full papers presented were carefully reviewed and selected from 58 submissions. The book offers topical sections on natural language processing; machine learning; knowledge representation, semantic web, and AI; neural networks; logic programming, theorem proving, and model checking; and vision and spatial reasoning.


Book Synopsis KI 2002: Advances in Artificial Intelligence by : Matthias Jarke

Download or read book KI 2002: Advances in Artificial Intelligence written by Matthias Jarke and published by Springer Science & Business Media. This book was released on 2002-09-04 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 25th Annual German conference on Artificial Intelligence, KI 2002, held in Aachen, Germany in September 2002. The 20 revised full papers presented were carefully reviewed and selected from 58 submissions. The book offers topical sections on natural language processing; machine learning; knowledge representation, semantic web, and AI; neural networks; logic programming, theorem proving, and model checking; and vision and spatial reasoning.

Machine Translation Summit

Machine Translation Summit

Author: Makoto Nagao

Publisher: IOS Press

Published: 1989

Total Pages: 248

ISBN-13: 9784274074455

DOWNLOAD EBOOK


Book Synopsis Machine Translation Summit by : Makoto Nagao

Download or read book Machine Translation Summit written by Makoto Nagao and published by IOS Press. This book was released on 1989 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Machine Translation

Neural Machine Translation

Author: Philipp Koehn

Publisher: Cambridge University Press

Published: 2020-06-18

Total Pages: 409

ISBN-13: 1108497322

DOWNLOAD EBOOK

Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.


Book Synopsis Neural Machine Translation by : Philipp Koehn

Download or read book Neural Machine Translation written by Philipp Koehn and published by Cambridge University Press. This book was released on 2020-06-18 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.

Machine Learning in Translation Corpora Processing

Machine Learning in Translation Corpora Processing

Author: Krzysztof Wolk

Publisher: CRC Press

Published: 2019-02-25

Total Pages: 209

ISBN-13: 0429588836

DOWNLOAD EBOOK

This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by mining comparable corpora.


Book Synopsis Machine Learning in Translation Corpora Processing by : Krzysztof Wolk

Download or read book Machine Learning in Translation Corpora Processing written by Krzysztof Wolk and published by CRC Press. This book was released on 2019-02-25 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by mining comparable corpora.

Advances in Empirical Translation Studies

Advances in Empirical Translation Studies

Author: Meng Ji

Publisher: Cambridge University Press

Published: 2019-06-13

Total Pages: 285

ISBN-13: 1108423272

DOWNLOAD EBOOK

Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.


Book Synopsis Advances in Empirical Translation Studies by : Meng Ji

Download or read book Advances in Empirical Translation Studies written by Meng Ji and published by Cambridge University Press. This book was released on 2019-06-13 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.