Kochendoerfer 1997: Neural models of language perception

Kochendoerfer 1997: Neural models of language perception

Contents BioMod Research - Lang-Acqu - Cortical Ling. - Aphasia Members - G. Kochend. - D. Veit - Kochend.    - 1997    - 1998    - 1998(2)    - 1999    - 2000 - Veit    - 2002 Comments Links

Guenter Kochendoerfer: Neuronale Modelle des Sprachverstehens. (Neural models of language perception.) Freiburg: HochschulVerlag 1997. The simulation models constructed in this book are intended to very closely meet the structure and behaviour of the brain. They are not comparable to current "brainstyle" simulations like the famous "artificial neural networks". This approach has some surprising (positive) consequences concerning the explanation of basic phenomena of language processing. A broad pattern of complex linguistic processes, e.g. lexical and syntactic processing, text comprehension, etc., are presented and explained by the models. Furthermore the author shows, how the neural structures worked out in this book are established by neural learning, including representations of blurred categories (prototype semantics). Insights obtained by the modelling of linguistic processes are used to get a deeper understanding of general processing strategies of the brain, memory and coherence. Not only linguistics (including speech pathologies) but the complete spectrum of cognitive sciences (computer sciences, biology, neurology, psychiatry, psychology, philosophy) may experience new perspectives. This title is unfortunately not available via Internet.

Contents:

Preface

1 Models: Basic concepts of modelling
1.1 The modelling concept
1.2 Correctness and completeness of models
1.3 Model hierarchies. Contents and empirical foundation of models
1.4 Model series. Explanational aspects of models
1.5 The value of modelling and simulation for cognitive sciences

2 Modularity: Modules, representations and accessibility
2.1 An abstract, general modular system
2.2 Properties of symbol manipulating systems
2.3 The thesis of a symbol manipulating character and of modular structures in artificial intelligence frameworks
2.4 The "hedgehog" Metaphor
2.5 Conclusion: About the impossibility of data transportation in the brain

3 Networks: Artificial neural networks and biology
3.1 Artificial intelligence
3.2 Biological neurons
3.3 Simulating "biological" neural networks
3.4 The attempt in "precising" connectionist models: basic problems
3.5 Conclusion

4 Lexical processing: Lexical access and lexical structures
4.1 Sound sequences
4.2 Vagueness, underdetermination and ambiguity
4.3 Phonological processes
4.4 Lexical structure
4.5 Simulating lexical access
4.6 Additional hypotheses, conclusions

5 Learning: Learning mechanisms and language acquisition in lexical structures
5.1 Reflections toward the concept of learning
5.2 Instances
5.3 Learning of instances
5.4 Simulation experiments on constructing instances
5.5 Learning of sequences
5.6 Simulation experiments on learning lexical word forms
5.7 Linking lexical word forms to concepts
5.8 Simulating lexical acquisition processes
5.9 Consequences

6 Syntax: a prototypical parser for syntactic structures of spoken language
6.1 The problem of representing sequential properties in "artificial neural networks"
6.2 Sequential representation with "biological" neurons
6.3 Sequences of constituents
6.4 Input and output of syntactical analyses
6.5 Congruency
6.6 A parser for analysing written sentences
6.7 A parser for analysing structures of spoken language
6.8 Conclusions

7 Prototypes: Prototype semantics in neural models
7.1 Learning instances as a basic principle of neural processing
7.2 A simulation experiment with surprising results
7.3 Comparison to concepts of prototype semantics
7.4 A simple example
7.5 Conclusion

8 Coherency: Text coherency, text semantics and text comprehension
8.1 Coherency as a property of the comprehension process
8.2 Basic structures
8.3 Simulating top-down-connections and watchdog
8.4 Predicates and propositional instances
8.5 Simulating the acquisition of propositional instances
8.6 Centralism and the structure of memory
8.7 Simulating the process of coherency control
8.8 Disturbing the process of coherency control
8.9 Lacks and perspectives

9 Speech production: Language comprehension and speech production, "Fischers Fritz fischt frische Fische"
9.1 A Prototype of a production model
9.2 Development of a neural structure of speech production (and perception) of lexical word forms
9.3 Fischers Fritz fischt frische Fische: Production of sequences out of sequences
9.4 Fischers Fritz fischt frische Fische: Fluency of speech and speech errors
9.5 Conclusion

10 Signs: Basic principles of language processing
10.1 Apparative basics
10.2 Relation between word form and concept
10.3 Arbitrarity
10.4 Linearity
10.5 Rules and redundancy

Literature

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Kochendoerfer 1997: Neural models of language perception

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