Incremental Conceptualization for Language Production

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A01=Markus Guhe
Anytime Algorithms
Author_Markus Guhe
Candidate List
Category=CFD
Category=JMA
Category=JMR
Cognitive Adequacy
cognitive architecture
cognitive science
computational linguistics
Concept Matcher
conceptual representation modeling
De Smedt
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eq_dictionaries-language-reference
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
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Event Threads
Focused Element
Follow
Incremental Algorithm
incremental conceptualization
Incremental Models
incremental processing
Indirect Feedback
Informational Encapsulation
Input Increment
Language Comprehension System
Language Production
linearization strategies
Parallelism Constraint
preverbal message generation
Preverbal Messages
psycholinguistics
Referential Net
referential nets
Semantic Representations
Sketch Maps
Subsumption Hierarchy
Vice Versa
Violates
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Product details

  • ISBN 9781138972506
  • Weight: 453g
  • Dimensions: 152 x 229mm
  • Publication Date: 16 Jan 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Incremental Conceptualization for Language Production discusses the simultaneous actions involved in thinking and speaking, as well as the piecemeal way in which individuals construct an internal representation of the external world and use this internal representation for speaking. Author Markus Guhe presents the first computational model that captures these observations in a cognitively adequate fashion. The volume is an innovative look at the mind’s process of producing semantic representations that can be transformed into language.   The first section of the book illustrates four stages of conceptualization: construction of a conceptual representation; selection of content to be verbalized; linearization of the selected content; and generation of preverbal messages. Guhe then analyzes incremental processing — processing that takes place in a piecemeal fashion — and offers a blueprint of incremental models while discussing the dimensions along which the processing principles and the blueprint varies. Finally, incremental processing and conceptualization merge to form the incremental conceptualiser model (inC). The effective use of inC is demonstrated through simulations carried out with the implementation of the model.   Intended for researchers in cognitive science, particularly cognitive modeling of language, this volume will also interest researchers in artificial intelligence, computational linguistics, psycholinguistics, and linguistics and psychology.

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