Connectionist Natural Language Processing

Connectionist Natural Language Processing : Readings from "Connection Science"

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Description

Connection science in a new information-processing paradigm which attempts to imitate the architecture and process of the brain, and brings together researchers from disciplines as diverse as computer science, physics, psychology, philosophy, linguistics, biology, engineering, neuroscience and AI. Work in Connectionist natural language processing (CNLP) is now expanding rapidly, yet much of the work is still only available in journals. To make this research more accessible, this work brings together an important and comprehensive set of articles from the journal "Connection Science", which represent the state of the art in Connectionist natural language processing, from speech recognition to discourse comprehension. While it is quintessentially Connectionist, it also deals with hybrid systems, and should be of interest to both theoreticians as well as computer modellers.
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Product details

  • Hardback | 384 pages
  • Dordrecht, Netherlands, United States
  • English
  • index
  • 0792315421
  • 9780792315421

Table of contents

Connectionism and congitive linguistics, C.L. Harris; a Connectionist model of motion and government on Chomsky's government-binding theory, J. Rager and G. Berg; syntactic transformations on distributed representations, D.J. Chalmers; syntactic neural networks, S.M. Lucas and R.I. Damper; incremental syntactic tree formation in human sentence processing - a cognitive architecture based on activation decay and simulated annealing, G. Kempen and T. Vosse; a hybrid symbolic/Connectionist model for noun phrase understanding, S. Wermter and W.G. Lehnert; Connectionism & determinism in a syntactic parser, S.C. Kwasny and K.A. Faisal; a single layer higher order neural net and its application to context free grammar recognition, P.J. Wyard and C. Nightingale; Connectionist language users, R.B. Allen; script recognition with hierarchical feature maps, R. Mikkulainen; learning distributed representations of conceptual knowledge and their application to script-based story processing, G. Lee et al; a hybrid model of script generation or getting the best from both worlds, S.M. Mannes and S.M. Doane; identification of topical entities in discourse - a Connectionist approach to attentional mechanisms in language, L.F.R. Karen; the role of similarity in Hungarian vowel harmony - a Connectionist account, M. Hare; representation and recognition of temporal patterns, R.F. Port; networks that learn about phonological feature persistence, M. Gasser and Chan-Do Lee; pronunciation of digit sequences in text-to-speech systems, W.A. Ainsworth and W.P. Arren.
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