Bayesian Natural Language Semantics and Pragmatics

✍ Scribed by Henk Zeevat, Hans-Christian Schmitz (eds.)

• Publisher: Springer International Publishing
• Year: 2015
• Tongue: English
• Leaves: 256
• Series: Language, Cognition, and Mind 2
• Edition: 1
• Category: Library

✦ Synopsis

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice’s contributions to pragmatics or in interpretation by abduction.

✦ Table of Contents

Front Matter....Pages i-xi
Perspectives on Bayesian Natural Language Semantics and Pragmatics....Pages 1-24
Causal Bayesian Networks, Signalling Games and Implicature of ‘More Than n’....Pages 25-42
Measurement-Theoretic Foundations of Logic for Better Questions and Answers....Pages 43-69
Conditionals, Conditional Probabilities, and Conditionalization....Pages 71-94
On the Probabilistic Notion of Causality: Models and Metalanguages....Pages 95-116
Shannon Versus Chomsky: Brain Potentials and the Syntax-Semantics Distinction....Pages 117-144
Orthogonality and Presuppositions: A Bayesian Perspective....Pages 145-178
Layered Meanings and Bayesian Argumentation: The Case of Exclusives....Pages 179-200
Variations on a Bayesian Theme: Comparing Bayesian Models of Referential Reasoning....Pages 201-220
Towards a Probabilistic Semantics for Vague Adjectives....Pages 221-246

✦ Subjects

Semantics; Computational Linguistics; Language Translation and Linguistics; Computer Appl. in Arts and Humanities