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Machine Translation: Technologies and Applications

Translation, Brains and the Computer

A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation

Authors: Scott, Bernard

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  • Addresses fundamental issues to solve the classic problems with machine translation
  • Recounts the little known background of early events affecting the history of machine translation
  • Identifies complexity as principal reason why machine translation has had limited success 
  • Illustrates problems of ambiguity and complexity in various present-day machine translation models, rule-based (RBMT), statistical (SMT) and neural MT (NMT)
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eBook $69.99
price for USA in USD (gross)
  • ISBN 978-3-319-76629-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-3-319-76628-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.99
price for USA in USD
  • ISBN 978-3-030-09538-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This book is about machine translation (MT) and the classic problems associated with this language technology. It examines the causes of these problems and, for linguistic, rule-based systems, attributes the cause to language’s ambiguity and complexity and their interplay in logic-driven processes. For non-linguistic, data-driven systems, the book attributes translation shortcomings to the very lack of linguistics. It then proposes a demonstrable way to relieve these drawbacks in the shape of a working translation model (Logos Model) that has taken its inspiration from key assumptions about psycholinguistic and neurolinguistic function. The book suggests that this brain-based mechanism is effective precisely because it bridges both linguistically driven and data-driven methodologies. It shows how simulation of this cerebral mechanism has freed this one MT model from the all-important, classic problem of complexity when coping with the ambiguities of language. Logos Model accomplishes this by a data-driven process that does not sacrifice linguistic knowledge, but that, like the brain, integrates linguistics within a data-driven process. As a consequence, the book suggests that the brain-like mechanism embedded in this model has the potential to contribute to further advances in machine translation in all its technological instantiations.

Reviews

“Natural language processing is one of the most rapidly evolving areas of artificial intelligence, and is the subject of this excellent book. … One of the important contributions of this valuable resource is its presentation and comparison of many current state-of-the-art machine translation systems available to the general public. Summing Up: Recommended. Advanced undergraduates through faculty and professionals.” (J. Brzezinski, Choice, Vol. 56 (6), February, 2019)


Table of contents (9 chapters)

Table of contents (9 chapters)

Buy this book

eBook $69.99
price for USA in USD (gross)
  • ISBN 978-3-319-76629-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-3-319-76628-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $89.99
price for USA in USD
  • ISBN 978-3-030-09538-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Translation, Brains and the Computer
Book Subtitle
A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation
Authors
Series Title
Machine Translation: Technologies and Applications
Series Volume
2
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-76629-4
DOI
10.1007/978-3-319-76629-4
Hardcover ISBN
978-3-319-76628-7
Softcover ISBN
978-3-030-09538-3
Series ISSN
2522-8021
Edition Number
1
Number of Pages
XVI, 241
Number of Illustrations
55 b/w illustrations
Topics