DevLex: A self-organizing neural network model of the development of lexicon

被引：0
|
作者：
Farkas, I [1 ]
Li, P [1 ]
机构：
[1] Univ Richmond, Dept Psychol, Richmond, VA 23173 USA
来源：
ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE | 2002年
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D O I：
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中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we present the DevLex model of language acquisition. DevLex consists of two self-organizing maps (a growing semantic map and a phonological map) that are connected via associative links. It simulates the early stages of lexical development in children, in particular, word confusion as evidenced in naming errors. The simulation results indicate that the rate of word confusion is modulated by developmental profile of vocabulary increase, word density of competing neighbors, and rate of lexical growth. These results match up with hypotheses from empirical research on lexical development.
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页码：2546 / 2551
页数：6
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