Learning Machine Translation PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Learning Machine Translation PDF full book. Access full book title Learning Machine Translation by Cyril Goutte. Download full books in PDF and EPUB format.
Author: Cyril Goutte
Publisher: MIT Press
ISBN: 0262072971
Category : Computers
Languages : en
Pages : 329
Get Book Here
Book Description
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Author: Cyril Goutte
Publisher: MIT Press
ISBN: 0262072971
Category : Computers
Languages : en
Pages : 329
Get Book Here
Book Description
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Author: Philipp Koehn
Publisher: Cambridge University Press
ISBN: 1108497322
Category : Computers
Languages : en
Pages : 409
Get Book Here
Book Description
Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.
Author: Krzysztof Wolk
Publisher: CRC Press
ISBN: 0429588836
Category : Computers
Languages : en
Pages : 205
Get Book Here
Book Description
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.
Author: Thierry Poibeau
Publisher: MIT Press
ISBN: 0262534215
Category : Computers
Languages : en
Pages : 298
Get Book Here
Book Description
A concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and major players in the industry. The dream of a universal translation device goes back many decades, long before Douglas Adams's fictional Babel fish provided this service in The Hitchhiker's Guide to the Galaxy. Since the advent of computers, research has focused on the design of digital machine translation tools—computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details. The book begins by discussing problems that must be solved during the development of a machine translation system and offering a brief overview of the evolution of the field. It then takes up the history of machine translation in more detail, describing its pre-digital beginnings, rule-based approaches, the 1966 ALPAC (Automatic Language Processing Advisory Committee) report and its consequences, the advent of parallel corpora, the example-based paradigm, the statistical paradigm, the segment-based approach, the introduction of more linguistic knowledge into the systems, and the latest approaches based on deep learning. Finally, it considers evaluation challenges and the commercial status of the field, including activities by such major players as Google and Systran.
Author: Yorick Wilks
Publisher: Springer Science & Business Media
ISBN: 0387727744
Category : Computers
Languages : en
Pages : 246
Get Book Here
Book Description
A history of machine translation (MT) from the point of view of a major writer and innovator in the field is the subject of this book. It details the deep differences between rival groups on how best to do MT, and presents a global perspective covering historical and contemporary systems in Europe, the US and Japan. The author considers MT as a fundamental part of Artificial Intelligence and the ultimate test-bed for all computational linguistics.
Author: Philipp Koehn
Publisher: Cambridge University Press
ISBN: 0521874157
Category : Computers
Languages : en
Pages : 447
Get Book Here
Book Description
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.
Author: Yong Cheng
Publisher: Springer Nature
ISBN: 9813297484
Category : Computers
Languages : en
Pages : 90
Get Book Here
Book Description
This book presents four approaches to jointly training bidirectional neural machine translation (NMT) models. First, in order to improve the accuracy of the attention mechanism, it proposes an agreement-based joint training approach to help the two complementary models agree on word alignment matrices for the same training data. Second, it presents a semi-supervised approach that uses an autoencoder to reconstruct monolingual corpora, so as to incorporate these corpora into neural machine translation. It then introduces a joint training algorithm for pivot-based neural machine translation, which can be used to mitigate the data scarcity problem. Lastly it describes an end-to-end bidirectional NMT model to connect the source-to-target and target-to-source translation models, allowing the interaction of parameters between these two directional models.
Author: Anoop Kunchukuttan
Publisher: CRC Press
ISBN: 1000422410
Category : Computers
Languages : en
Pages : 215
Get Book Here
Book Description
Machine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation. Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.
Author: Lynne Bowker
Publisher: Emerald Group Publishing
ISBN: 1787567230
Category : Computers
Languages : en
Pages : 97
Get Book Here
Book Description
Lynne Bowker and Jairo Buitrago Ciro introduce the concept of machine translation literacy, a new kind of literacy for scholars and librarians in the digital age. This book is a must-read for researchers and information professionals eager to maximize the global reach and impact of any form of scholarly work.
Author: Sergei Nirenburg
Publisher: IOS Press
ISBN: 9789051990744
Category : Computers
Languages : en
Pages : 338
Get Book Here
Book Description
