This book presents recent advances by leading researchers in computational modelling of language acquisition. The contributors have been drawn from departments of linguistics, cognitive science, psychology, and computer science. They show what light can be thrown on fundamental problems when powerful computational techniques are combined with real data. The book considers the extent to which linguistic structure is readily available in the environment, the degree to which language learning is inductive or deductive, and the power of different modelling formalisms for different problems and…mehr
This book presents recent advances by leading researchers in computational modelling of language acquisition. The contributors have been drawn from departments of linguistics, cognitive science, psychology, and computer science. They show what light can be thrown on fundamental problems when powerful computational techniques are combined with real data. The book considers the extent to which linguistic structure is readily available in the environment, the degree to which language learning is inductive or deductive, and the power of different modelling formalisms for different problems and approaches. It will appeal to linguists, psychologists, cognitive scientists working in language acquisition,and to those involved in computational modelling in linguistic and behavioral science.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Peter Broeder is Assistant Professor at Tilburg University where his research involves unravelling processes of language change among ethnic minority groups. Jaap Murre is a Research Fellow in the Department of Psychology, University of Amsterdam. Previously he worked as a scientist at the Applied Psychology Unit of the Medical Research Council in Cambridge. Dr. Murre also heads a research group sponsored by a PIONIER grant from the Netherlands Organization for Scientific Research (NWO).
Inhaltsangabe
* Chapter 1: Introduction * Part I: Words * Chapter 2: Lexicalist Connectionism * Chapter 3: Are SRNs Sufficient for Modelling Language Acquisition? * Chapter 4: A Distributed, Yet Symbolic Model for Text-to-Speech Processing * Chapter 5: "Lazy Learning": A Comparison of Natural and Machine Learning of Word Stress * Part II: Word Formation * Chapter 6: Statistical and Connectionist Modelling of the Development of Speech Segmentation * Chapter 7: Learning Word-to-Meaning Mappings * Chapter 8: Children's Overregularization and its Implication for Cognition * Chapter 9: The Performance of a Recurrent Network with Short Term Memory Capacity Learning the German -S Plural * Chapter 19: A Cross-Linguistic Comparison of Single and Dual-Route Models of Inflectional Morphology * Part III: Word Order * Chapter 11: Formal Models for Learning in the Principles and Parameters Framework * Chapter 12: An Output-as-Input Hypothesis for Language Acquisition: Arguments, Model, Evidence
* Chapter 1: Introduction * Part I: Words * Chapter 2: Lexicalist Connectionism * Chapter 3: Are SRNs Sufficient for Modelling Language Acquisition? * Chapter 4: A Distributed, Yet Symbolic Model for Text-to-Speech Processing * Chapter 5: "Lazy Learning": A Comparison of Natural and Machine Learning of Word Stress * Part II: Word Formation * Chapter 6: Statistical and Connectionist Modelling of the Development of Speech Segmentation * Chapter 7: Learning Word-to-Meaning Mappings * Chapter 8: Children's Overregularization and its Implication for Cognition * Chapter 9: The Performance of a Recurrent Network with Short Term Memory Capacity Learning the German -S Plural * Chapter 19: A Cross-Linguistic Comparison of Single and Dual-Route Models of Inflectional Morphology * Part III: Word Order * Chapter 11: Formal Models for Learning in the Principles and Parameters Framework * Chapter 12: An Output-as-Input Hypothesis for Language Acquisition: Arguments, Model, Evidence
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