Crossroads between Contrastive Linguistics, Translation Studies and Machine Translation


Book Description

Contrastive Linguistics (CL), Translation Studies (TS) and Machine Translation (MT) have common grounds: They all work at the crossroad where two or more languages meet. Despite their inherent relatedness, methodological exchange between the three disciplines is rare. This special issue touches upon areas where the three fields converge. It results directly from a workshop at the 2011 German Association for Language Technology and Computational Linguistics (GSCL) conference in Hamburg where researchers from the three fields presented and discussed their interdisciplinary work. While the studies contained in this volume draw from a wide variety of objectives and methods, and various areas of overlaps between CL, TS and MT are addressed, the volume is by no means exhaustive with regard to this topic. Further cross-fertilisation is not only desirable, but almost mandatory in order to tackle future tasks and endeavours.}




Readings in Machine Translation


Book Description

The field of machine translation (MT) - the automation of translation between human languages - has existed for more than 50 years. MT helped to usher in the field of computational linguistics and has influenced methods and applications in knowledge representation, information theory, and mathematical statistics.




Translation Engines: Techniques for Machine Translation


Book Description

Machine translation (MT) is the area of computer science and applied linguistics dealing with the translation of human languages such as English and German. MT on the Internet has become an important tool by providing fast, economical and useful translations. With globalisation and expanding trade, demand for translation is set to grow. Translation Engines covers theoretical and practical aspects of MT, both classic and new, including: - Character sets and formatting languages - Translation memory - Linguistic and computational foundations - Basic computational linguistic techniques - Transfer and interlingua MT - Evaluation Software accompanies the text, providing readers with hands on experience of the main algorithms.




An Introduction to Machine Translation


Book Description

The translation of foreign language texts by computers was one of the first tasks that the pioneers of computing and artificial intelligence set themselves. Machine translation is again becoming an important field of research and development as the need for translations of technical and commercial documentation is growing beyond the capacity of the translation profession.




Neural Machine Translation


Book Description

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







Machine Translation


Book Description




Machine Translation


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.







Syntax-based Statistical Machine Translation


Book Description

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.