This book addresses one of the most famous and controversial arguments in the study of language and mind, the Poverty of the Stimulus. Presented by Chomsky in 1968, the argument holds that children do not receive enough evidence to infer the existence of core aspects of language, such as the dependence of linguistic rules on hierarchical phrase structure. The argument strikes against empiricist accounts of language acquisition and supports the conclusion that knowledge of some aspects of grammar must be innate. In the first part of Rich Grammars from Poor Inputs, contributors consider the general issues around the POS argument, review the empirical data, and offer new and plausible explanations. This is followed by a discussion of the the processes of language acquisition, and observed 'gaps' between adult and child grammar, concentrating on the late spontaneous acquisition by children of some key syntactic principles, basically, though not exclusively, between the ages of 5 to 9. Part 3 widens the horizon beyond language acquisition in the narrow sense, examining the natural development of reading and writing and of the child's growing sensitivity for the fine arts.

Rich Languages From Poor Inputs

Reference

Piattelli-Palmarini, Massimo

Berwick, Robert C.

Words, Language & Grammar

Oxford University Press

Written primarily from the perspective of computational theory, Grammatical Basis of Linguistic Performance presents a synthesis of some major recent developments in grammatical theory and its application to models of language performance.

The grammatical basis of linguistic performance: Language use and acquisition (Current studies in linguistics series)

Language Study & Reference

MIT Press]

This landmark work in computational linguistics is of great importance both theoretically and practically because it shows that much of English grammar can be learned by a simple program.The Acquisition of Syntactic Knowledge investigates the central questions of human and machine cognition: How do people learn language? How can we get a machine to learn language? It first presents an explicit computational model of language acquisition which can actually learn rules of English syntax given a sequence of grammatical, but otherwise unprepared, sentences.It shows that natural languages are designed to be easily learned and easily processed-an exciting breakthrough from the point of view of artificial intelligence and the design of expert systems because it shows how extensive knowledge might be acquired automatically, without outside intervention. Computationally, the book demonstrates how constraints that may be reasonably assumed to aid sentence processing also aid language acquisition.Chapters in the book's second part apply computational methods to the general problem of developmental growth, particularly the thorny problem of the interaction between innate genetic endowment and environmental input, with the intent of uncovering the constraints on the acquisition of syntactic knowledge.A number of "mini-theories" of learning are incorporated in this study of syntax with results that should appeal to a wide range of scholarly interests. These include how lexical categories, phonological rule systems, and phrase structure rules are learned; the role of semantic-syntactic interaction in language acquisition; how a "parameter setting" model may be formalized as a learning procedure; how multiple constraints (from syntax, thematic knowledge, or phrase structure) interact to aid acquisition; how transformational-type rules may be learned; and, the role of lexical ambiguity in language acquisition.Robert Berwick is an assistant professor in the Department of Electrical Engineering and Computer Science at MIT. The Acquisition of Syntactic Knowledge is sixteenth in the Artificial Intelligence Series, edited by Patrick Winston and Michael Brady.

The Acquisition of Syntactic Knowledge (Artificial Intelligence)

Computers & Technology

Computer Science

Mit Pr

Computational Complexity and Natural Language heralds an entirely new way of looking at grammatical systems. It applies the recently developed computer science tool of complexity theory to the study of natural language. A unified and coherent account emerges of how complexity theory can probe the information-processing structure of grammars, discovering why a grammar is easy or difficult to process and suggesting where to look for additional grammatical constraints. For the linguist or cognitive scientist, the book presents a nontechnical introduction to complexity theory and discusses its strengths, its weaknesses, and how it can be used to study grammars. For the computer scientist, it offers a more sophisticated and efficient computational analysis of linguistic theories. Given the variety of new techniques rising from complexity theory, the authors foresee a developing cooperation among linguists, cognitive scientists, and computer scientists toward understanding the nature of human language. The book also describes a set of case studies that use complexity theory to analyze grammatical problems. And it examines several grammatical systems currently of interest to computational linguists - including spelling-change/dictionary lookup and morphological analysis, agreement processes in natural language, and lexical-functional grammar - demonstrating how complexity analysis can illuminate and improve each one. All of the authors are at the MIT Artificial Intelligence Laboratory. Robert C. Berwick is an Associate Professor in the Department of Electrical Engineering and Computer Science. A Bradford Book.

Computational Complexity and Natural Language

Health, Fitness & Dieting

Ristad, Eric Sven

Barton, G. Edward, Jr.

Psychology & Counseling

Bradford Books

Berwick and Chomsky draw on recent developments in linguistic theory to offer an evolutionary account of language and humans' remarkable, species-specific ability to acquire it.
“A loosely connected collection of four essays that will fascinate anyone interested in the extraordinary phenomenon of language.” ―New York Review of Books
We are born crying, but those cries signal the first stirring of language. Within a year or so, infants master the sound system of their language; a few years after that, they are engaging in conversations. This remarkable, species-specific ability to acquire any human language―“the language faculty”―raises important biological questions about language, including how it has evolved. This book by two distinguished scholars―a computer scientist and a linguist―addresses the enduring question of the evolution of language.
Robert Berwick and Noam Chomsky explain that until recently the evolutionary question could not be properly posed, because we did not have a clear idea of how to define “language” and therefore what it was that had evolved. But since the Minimalist Program, developed by Chomsky and others, we know the key ingredients of language and can put together an account of the evolution of human language and what distinguishes us from all other animals.
Berwick and Chomsky discuss the biolinguistic perspective on language, which views language as a particular object of the biological world; the computational efficiency of language as a system of thought and understanding; the tension between Darwin's idea of gradual change and our contemporary understanding about evolutionary change and language; and evidence from nonhuman animals, in particular vocal learning in songbirds.

Why Only Us: Language and Evolution

CHOMSKY, Noam.

The Acquisition of Syntactic Knowledge (Artificial Intelligence Series)

The MIT Press

Computational Complexity and Natural Language heralds an entirely new way of looking at grammatical systems. It applies the recently developed computer science tool of complexity theory to the study of natural language. A unified and coherent account emerges of how complexity theory can probe the information-processing structure of grammars, discovering why a grammar is easy or difficult to process and suggesting where to look for additional grammatical constraints. For the linguist or cognitive scientist, the book presents a nontechnical introduction to complexity theory and discusses its strengths, its weaknesses, and how it can be used to study grammars. For the computer scientist, it offers a more sophisticated and efficient computational analysis of linguistic theories. Given the variety of new techniques rising from complexity theory, the authors foresee a developing cooperation among linguists, cognitive scientists, and computer scientists toward understanding the nature of human language. The book also describes a set of case studies that use complexity theory to analyze grammatical problems. And it examines several grammatical systems currently of interest to computational linguists - including spelling-change/dictionary lookup and morphological analysis, agreement processes in natural language, and lexical-functional grammar - demonstrating how complexity analysis can illuminate and improve each one.A Bradford Book.

Computational Complexity and Natural Language (Computational Models of Cognition and Perception)

Barton, G. Edward

Software

A mathematical formalization of Chomsky’s theory of Merge in generative linguistics.\nThe Minimalist Program advanced by Noam Chomsky thirty years ago, focusing on the biological nature of human language, has played a central role in our modern understanding of syntax. One key to this program is the notion that the hierarchical structure of human language syntax consists of a single operation Merge. For the first time, Mathematical Structure of Syntactic Merge presents a complete and precise mathematical formalization of Chomsky’s most recent theory of Merge. It both furnishes a new way to explore Merge’s important linguistic implications clearly while also laying to rest any fears that the Minimalist framework based on Merge might itself prove to be formally incoherent.\nIn this book, Matilde Marcolli, Noam Chomsky, and Robert C. Berwick prove that Merge can be described as a very particular kind of highly structured algebra. Additionally, the book shows how Merge can be placed within a consistent framework that includes both a syntactic-semantic interface that realizes Chomsky’s notion of a conceptual-intentional interface, and an externalization system that realizes language-specific constraints. The syntax-semantics interface encompasses many current semantical theories and offers deep insights into the ways that modern “large language models” work, proving that these do not undermine in any way the scientific theories of language based on generative grammar.

Mathematical Structure of Syntactic Merge: An Algebraic Model for Generative Linguistics (Linguistic Inquiry Monographs)

Marcolli, Matilde

Merge and the Strong Minimalist Thesis (Elements in Generative Syntax)

The goal of this contribution to the Elements series is to closely examine Merge, its form, its function, and its central role in current linguistic theory. It explores what it does (and does not do), why it has the form it has, and its development over time. The basic idea behind Merge is quite simple. However, Merge interacts, in intricate ways, with other components including the language's interfaces, laws of nature, and certain language-specific conditions. Because of this, and because of its fundamental place in the human faculty of language, this Element's focus on Merge provides insights into the goals and development of generative grammar more generally, and its prospects for the future.

Kitahara, Hisatsugu

Seely, T. Daniel

Fong, Sandiway

Huybregts, M. A. C.

McInnerney, Andrew

Sugimoto, Yushi

Cambridge University Press

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