Probabilistic Linguistics

Probabilistic Linguistics
Author: Rens Bod
Publisher: MIT Press
Total Pages: 468
Release: 2003
Genre: Language Arts & Disciplines
ISBN: 9780262523387


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For the past forty years, linguistics has been dominated by the idea that language is categorical and linguistic competence discrete. It has become increasingly clear, however, that many levels of representation, from phonemes to sentence structure, show probabilistic properties, as does the language faculty. Probabilistic linguistics conceptualizes categories as distributions and views knowledge of language not as a minimal set of categorical constraints but as a set of gradient rules that may be characterized by a statistical distribution. Whereas categorical approaches focus on the endpoints of distributions of linguistic phenomena, probabilistic approaches focus on the gradient middle ground. Probabilistic linguistics integrates all the progress made by linguistics thus far with a probabilistic perspective. This book presents a comprehensive introduction to probabilistic approaches to linguistic inquiry. It covers the application of probabilistic techniques to phonology, morphology, semantics, syntax, language acquisition, psycholinguistics, historical linguistics, and sociolinguistics. It also includes a tutorial on elementary probability theory and probabilistic grammars.


Probabilistic Linguistics
Language: en
Pages: 468
Authors: Rens Bod
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2003 - Publisher: MIT Press

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For the past forty years, linguistics has been dominated by the idea that language is categorical and linguistic competence discrete. It has become increasingly
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Almost four decades have passed since "Formal Grammars "first appeared in 1974. At that time it was still possible to rather comprehensively review for (psycho)
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Type: BOOK - Published: 2020-12-03 - Publisher: Cambridge University Press

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This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, securit
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What counts as evidence in linguistics? This question is addressed by the contributions to the present volume (originally published as a Special Issue of Studie