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  Modeling human word recognition with sequences of artificial neurons

Wittenburg, P., van Kuijk, D., & Dijkstra, T. (1996). Modeling human word recognition with sequences of artificial neurons. In C. von der Malsburg, W. von Seelen, J. C. Vorbrüggen, & B. Sendhoff (Eds.), Artificial Neural Networks — ICANN 96. 1996 International Conference Bochum, Germany, July 16–19, 1996 Proceedings (pp. 347-352). Berlin: Springer.

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Wittenburg_1996.pdf (Publisher version), 379KB
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 Creators:
Wittenburg, Peter1, Author           
van Kuijk, D., Author
Dijkstra, T., Author
Affiliations:
1Technical Group, MPI for Psycholinguistics, Max Planck Society, ou_55220              

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 Abstract: A new psycholinguistically motivated and neural network based model of human word recognition is presented. In contrast to earlier models it uses real speech as input. At the word layer acoustical and temporal information is stored by sequences of connected sensory neurons which pass on sensor potentials to a word neuron. In experiments with a small lexicon which includes groups of very similar word forms, the model meets high standards with respect to word recognition and simulates a number of wellknown psycholinguistical effects.

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Language(s): eng - English
 Dates: 1996
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/3-540-61510-5_61
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Title: Artificial Neural Networks — ICANN 96. 1996 International Conference Bochum, Germany, July 16–19, 1996 Proceedings
Source Genre: Proceedings
 Creator(s):
von der Malsburg, Christoph, Editor
von Seelen, , Werner, Editor
Vorbrüggen, , Jan C., Editor
Sendhoff , Bernard, Editor
Affiliations:
-
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 347 - 352 Identifier: ISBN: 978-3-540-61510-1