Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation: 2 (Machine Translation: Technologies and Applications, 2) - Image 1

£99.37

Springer Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation: 2 (Machine Translation: Technologies and Applications, 2)

Name: Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation: 2 (Machine Translation: Technologies and Applications, 2)
Brand: Springer
Price: 99.42 GBP
Availability: InStock

AI & Machine Learning

Price History & Forecast

Last 31 days • 31 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 31 days • 1 price levels

Days at Price

Price Analysis

Most common price: £99 (31 days, 100.0%)

Price range: £99 - £99

Price levels: 1 different prices over 31 days

Description

Product Description 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. Review “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) From the Back Cover 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.

Product Specifications

Brand: Springer
Format: Paperback
ASIN: 303009538X
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 28 December 2018
Listed Since: 28 December 2018

Barcode

No barcode data available

Springer Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation: 2 (Machine Translation: Technologies and Applications, 2)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Translation, Brains and the Computer: A Neurolinguistic Solution to Ambiguity and Complexity in Machine Translation: 2 (Machine Translation: Technologies and Applications, 2)

The Natural Language for Artificial Intelligence (Cognitive Data Science in Sustainable Computing)

New Advances in Translation Technology: Applications and Pedagogy (New Frontiers in Translation Studies)

Logic and Algorithms in Computational Linguistics 2018 (LACompLing2018): 860 (Studies in Computational Intelligence, 860)

Technology Implementation in Second Language Teaching and Translation Studies: New Tools, New Approaches (New Frontiers in Translation Studies)

Machine Translation and Transliteration involving Related, Low-resource Languages

The KBMT Project: A Case Study in Knowledge-Based Machine Translation (Representation and Reasoning)

Computational Cognitive Modeling and Linguistic Theory: 6 (Language, Cognition, and Mind, 6)

Intelligent Language Tutors: Theory Shaping Technology

Language and Computers

Explorations in Empirical Translation Process Research: 3 (Machine Translation: Technologies and Applications, 3)

Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series)

Language in Cognition: Uncovering Mental Structures and the Rules Behind Them

Natural Language Processing in Artificial Intelligence ― NLPinAI 2021: 999 (Studies in Computational Intelligence, 999)

Research on Translator and Interpreter Training: A Collective Volume of Bibliometric Reviews and Empirical Studies on Learners (New Frontiers in Translation Studies)

Demystifying the Brain: A Computational Approach

Machine Translation: Its Scope and Limits

Human Brain Theory: Information-Commutation Device of the Brain & Principles of its Work & Modeling

On the Construction of Artificial Brains

Human Translators in the Machine Age (Routledge Focus on Translation and Interpreting Studies)

Psycholinguistics and Neurolinguistics: A Survey on the Neural Basis of Language Acquisition - Studies on Atypical Neurodevelopment, Neuroimaging, and Neurocognitive Aspects of Modern Linguistics

Neural Network Methods for Natural Language Processing (Synthesis Lectures on Human Language Technologies)

Formalizing Natural Languages: The NooJ Approach (Cognitive Science)

New Perspectives on Corpus Translation Studies (New Frontiers in Translation Studies)