Lexical Priming proposes a radical new theory of the lexicon, which amounts to a completely new theory of language based on how words are used in the real world. Here they are not confined to the definitions given to them in dictionaries but instead interact with other words in common patterns of use. Using concrete statistical evidence from a corpus of newspaper English, but also referring to travel writing and literary text, the author argues that words are 'primed' for use through our experience with them, so that everything we know about a word is a product of our encounters with it. This knowledge explains how speakers of a language succeed in being fluent, creative and natural.

This book shows that over forty years of psychological laboratory-based research support the claims of the Lexical Priming Theory. It examines how Lexical Priming applies to the use of spoken English as the book provides evidence that Lexical Priming is found in everyday spoken conversations.

This book explores the interconnections between linguistics and Artificial Intelligence (AI) research, their mutually influential theories and developments, and the areas where these two groups can still learn from each other. It begins with a brief history of artificial intelligence theories focusing on figures including Alan Turing and M. Ross Quillian and the key concepts of priming, spread-activation and the semantic web. The author details the origins of the theory of lexical priming in early AI research and how it can be used to explain structures of language that corpus linguists have uncovered. He explores how the idea of mirroring the mind’s language processing has been adopted to create machines that can be taught to listen and understand human speech in a way that goes beyond a fixed set of commands. In doing so, he reveals how the latest research into the semantic web and Natural Language Processing has developed from its early roots. The book moves on to describe how the technology has evolved with the adoption of inference concepts, probabilistic grammar models, and deep neural networks in order to fine-tune the latest language-processing and translation tools. This engaging book offers thought-provoking insights to corpus linguists, computational linguists and those working in AI and NLP.

Published in 2005, Michael Hoey’s Lexical Priming – A new theory of words and language introduced a completely new theory of language based on how words are used in the real world. In the ten years that have passed, the theory has since gained traction in the field of corpus-linguistics. This volume brings together some of the most important contributions to the theory, in areas such as language teaching and learning, discourse analysis, stylistics as well as the design of language learning software. Crucially, this book introduces aspects of the language that have so far been given less focus in lexical priming, such as spoken language, figurative language, forced primings, priming as predictor of genre, and historical primings. The volume also focuses on applying the lexical priming theory to languages other than English including Mandarin Chinese and Finnish.

Masked priming has a short and somewhat controversial history. When used as a tool to study whether semantic processing can occur in the absence of conscious awareness, considerable debate followed, mainly about whether masked priming truly tapped unconscious processes. For research into other components of visual word processing, however - in particular, orthographic, phonological, and morphological - a general consensus about the evidence provided by masked priming results has emerged. This book contains thirteen original chapters in which these three components of visual word processing are examined using the masked priming procedure. The chapters showcase the advantages of masked priming as an alternative to more standard methods of studying language processing that require comparisons of matched items. Based on a recent conference, this book offers up-to-date research findings, and would be valuable to researchers and students of word recognition, psycholinguistics, or reading.

A lexically based, corpus-driven theoretical approach to meaning in language that distinguishes between patterns of normal use and creative exploitations of norms. In Lexical Analysis, Patrick Hanks offers a wide-ranging empirical investigation of word use and meaning in language. The book fills the need for a lexically based, corpus-driven theoretical approach that will help people understand how words go together in collocational patterns and constructions to make meanings. Such an approach is now possible, Hanks writes, because of the availability of new forms of evidence (corpora, the Internet) and the development of new methods of statistical analysis and inferencing. Hanks offers a new theory of language, the Theory of Norms and Exploitations (TNE), which makes a systematic distinction between normal and abnormal usage—between rules for using words normally and rules for exploiting such norms in metaphor and other creative use of language. Using hundreds of carefully chosen citations from corpora and other texts, he shows how matching each use of a word against established contextual patterns plays a large part in determining the meaning of an utterance. His goal is to develop a coherent and practical lexically driven theory of language that takes into account the immense variability of everyday usage and that shows that this variability is rule governed rather than random. Such a theory will complement other theoretical approaches to language, including cognitive linguistics, construction grammar, generative lexicon theory, priming theory, and pattern grammar.

The most frequently used words in English are highly ambiguous; for example, Webster's Ninth New Collegiate Dictionary lists 94 meanings for the word "run" as a verb alone. Yet people rarely notice this ambiguity. Solving this puzzle has commanded the efforts of cognitive scientists for many years. The solution most often identified is "context": we use the context of utterance to determine the proper meanings of words and sentences. The problem then becomes specifying the nature of context and how it interacts with the rest of an understanding system. The difficulty becomes especially apparent in the attempt to write a computer program to understand natural language. Lexical ambiguity resolution (LAR), then, is one of the central problems in natural language and computational semantics research. A collection of the best research on LAR available, this volume offers eighteen original papers by leading scientists. Part I, Computer Models, describes nine attempts to discover the processes necessary for disambiguation by implementing programs to do the job. Part II, Empirical Studies, goes into the laboratory setting to examine the nature of the human disambiguation mechanism and the structure of ambiguity itself. A primary goal of this volume is to propose a cognitive science perspective arising out of the conjunction of work and approaches from neuropsychology, psycholinguistics, and artificial intelligence--thereby encouraging a closer cooperation and collaboration among these fields. Lexical Ambiguity Resolution is a valuable and accessible source book for students and cognitive scientists in AI, psycholinguistics, neuropsychology, or theoretical linguistics.