Connectionist Models of Memory and Language
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Connectionist Models of Memory and Language

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Description

Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time. The book is divided into four sections: Memory; Reading; Computation and statistics; Speech and audition. Each section is introduced and set in context by the editors, allowing a wide range of language and memory issues to be addressed in one volume. This authoritative advanced level book will still be of interest for all engaged in connectionist research and the related areas of cognitive science concerned with language and memory.show more

Product details

  • Paperback | 368 pages
  • 156 x 234 x 18.8mm | 648g
  • Taylor & Francis Ltd
  • ROUTLEDGE
  • London, United Kingdom
  • English
  • black & white illustrations
  • 1138971537
  • 9781138971530

Table of contents

Preface. Acknowledgements. Contributors. Section 1: Memory 1. David W. Glasspool Competitive Queuing and the Articulatory Loop 2. Dimitrios Bairaktaris Temporal Chunking and Synchronization Using a Modular Recurrent Network Architecture 3. Gordon D. A. Brown, Tim Preece, Charles Hulme Learning to Learn in a Connectionist Network: The Development of Associative Learning 4. Noel E. Sharkey and Amanda J.C. Sharkey Interference and Discrimination in Neural Net Memory 5. Jacob M.J. Murre Transferof Learning in Back-propagation and in Related Neural Network Models 6. Joseph P. Levy and Dimitrios Bairaktaris Interactions Between Short- and Long-term Weights: Applications for Cognitive Modelling Section 2: Reading 7. Robert I. Damper Self-learning and Connectionist Approaches to Text-Phoneme Conversion 8. David C. Plaut, James L. McClelland Mark S. Seidenberg Reading Exception Words and Pseudowords: Are Two Routes Really Necessary? 9. John A. Bullinaria Neural Network Models of Reading: Solving the Alignment Problem without Wickelfeatures Section 3: Computation and Statistics 10. Robert W. Kentridge Cortical Neurocomputation, Language and Cognition 11. Nick Chater Neural Networks: The New Statistical Models of Mind 12. Steve Finch, Nick Chater, Martin Redington Acquiring Syntactic Information from Distributional Statistics Section 4: Speech and Audition 13. Leslie S. Smith Onset/Offset Filters for the Segmentation of Sound 14. Mukhlis Abu-Bakar and Nick Chater Time-warping Tasks and Recurrent Neural Networks 15. Paul Cairns, Richard Shillcock, Nick Chater, Joseph P. Levy Bottom-up Connectionist Modelling of Speech 16. Trevor A. Harley and Siobhan B.G. MacAndrew. Index.show more