TY  - UNPB
ID  - cogprints4739
UR  - http://cogprints.org/4739/
A1  - Moscoso del Prado Martin, Dr Fermin
A1  - Baayen, Prof R. Harald
TI  - A broad-coverage distributed connectionist model of visual word recognition
Y1  - 2005///
N2  - In this study we describe a distributed connectionist model of morphological processing, covering a realistically sized sample of the English language. The purpose of this model is to explore how effects of discrete, hierarchically structured morphological paradigms, can arise as a result of the statistical sub-regularities in the mapping between
word forms and word meanings. We present a model that learns to produce at its output a realistic semantic representation of a word, on presentation of a distributed representation of its orthography. After training, in three experiments, we compare the outputs of the model with the lexical decision latencies for large sets of English nouns and verbs. We show that the model has developed detailed representations of morphological structure, giving rise to effects analogous to those observed in visual lexical decision experiments. In addition, we show how the association between word form and word meaning also
give rise to recently reported differences between regular and irregular verbs, even in their completely regular present-tense forms. We interpret these results as underlining the key importance for lexical processing of the statistical regularities in the mappings between form and meaning.

AV  - public
KW  - Distributed connectionist
KW  -  family size
KW  -  inflectional entropy
KW  -  co-occurrence vectors
ER  -

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