Learning Machine Translation

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.

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 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

Download or read book Neural Machine Translation written by Philipp Koehn and published by . This book was released on 2020 with total page 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.

Download or read book Machine Translation written by Thierry Poibeau and published by MIT Press. This book was released on 2017-09-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Download or read book Learning Machine Translation written by Cyril Goutte and published by MIT Press. This book was released on 2009 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.

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 205 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.