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Computational Linguistics

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Based on an introductory course on natural-language semantics, this book provides an introduction to type-logical grammar and the range of linguistic phenomena that can be handled in categorial grammar. It also contains a great deal of original work on categorial grammar and its application to natural-language semantics. The author chose the type-logical categorial grammar as his grammatical basis because of its broad syntactic coverage and its strong linkage of syntax and semantics.

A Study in Cognitive Science

To communicate, speakers need to make it clear what they are talking about. The act of referring, which anchors words to things, is a fundamental aspect of language. In this book, Kees van Deemter shows that computational models of reference offer attractive tools for capturing the complexity of referring.

A Theory of Linguistic Computation and Storage

Language allows us to express and comprehend an unbounded number of thoughts. This fundamental and much-celebrated property is made possible by a division of labor between a large inventory of stored items (e.g., affixes, words, idioms) and a computational system that productively combines these stored units on the fly to create a potentially unlimited array of new expressions. A language learner must discover a language’s productive, reusable units and determine which computational processes can give rise to new expressions.

From Neural Computation to Optimality-Theoretic Grammar Volume I: Cognitive Architecture
From Neural Computation to Optimality-Theoretic Grammar Volume II: Linguistic and Philosophical Implications

Despite their apparently divergent accounts of higher cognition, cognitive theories based on neural computation and those employing symbolic computation can in fact strengthen one another. To substantiate this controversial claim, this landmark work develops in depth a cognitive architecture based in neural computation but supporting formally explicit higher-level symbolic descriptions, including new grammar formalisms.

The nature of the interplay between language learning and the evolution of a language over generational time is subtle. We can observe the learning of language by children and marvel at the phenomenon of language acquisition; the evolution of a language, however, is not so directly experienced. Language learning by children is robust and reliable, but it cannot be perfect or languages would never change—and English, for example, would not have evolved from the language of the Anglo-Saxon Chronicles.

Optimal and Costly Computations

In this monograph Tanya Reinhart discusses strategies enabling the interface of different cognitive systems, which she identifies as the systems of concepts, inference, context, and sound. Her point of departure is Noam Chomsky's hypothesis that language is optimally designed—namely, that in many cases, the bare minimum needed for constructing syntactic derivations is sufficient for the full needs of the interface. Deviations from this principle are viewed as imperfections.

This book addresses a fundamental software engineering issue, applying formal techniques and rigorous analysis to a practical problem of great current interest: the incorporation of language-specific knowledge in interactive programming environments. It makes a basic contribution in this area by proposing an attribute-grammar framework for incremental semantic analysis and establishing its algorithmic foundations.

The field of machine translation (MT)—the automation of translation between human languages—has existed for more than fifty years. MT helped to usher in the field of computational linguistics and has influenced methods and applications in knowledge representation, information theory, and mathematical statistics.

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.

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