Overview
- 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)
Part of the book series: Machine Translation: Technologies and Applications (MATRA, volume 2)
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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.
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Table of contents (9 chapters)
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Front Matter
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Part I
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Front Matter
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Part II
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Front Matter
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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)
Authors and Affiliations
Bibliographic Information
Book Title: Translation, Brains and the Computer
Book Subtitle: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation
Authors: Bernard Scott
Series Title: Machine Translation: Technologies and Applications
DOI: https://doi.org/10.1007/978-3-319-76629-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-76628-7Published: 15 June 2018
Softcover ISBN: 978-3-030-09538-3Published: 28 December 2018
eBook ISBN: 978-3-319-76629-4Published: 06 June 2018
Series ISSN: 2522-8021
Series E-ISSN: 2522-803X
Edition Number: 1
Number of Pages: XVI, 241
Number of Illustrations: 55 b/w illustrations
Topics: Natural Language Processing (NLP), Computational Linguistics, Psycholinguistics