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Original scientific paper

Claudia Marzi; This email address is being protected from spambots. You need JavaScript enabled to view it.; National Research Council, Pisa, Italy

Marcello Ferro; This email address is being protected from spambots. You need JavaScript enabled to view it.; National Research Council, Pisa, Italy

Emmanuel Keuleers; This email address is being protected from spambots. You need JavaScript enabled to view it.; Ghent University, Belgium

 

Abstract

 

The extent to which a symbolic time–series (a sequence of sounds or letters) is a typical
word of a language, referred to as WORDLIKENESS, has been shown to have effects in speech
perception and production, reading proficiency, lexical development and lexical access,
short–term and long–term verbal memory. Two quantitative models have been suggested to
account for these effects: serial phonotactic probabilities (the likelihood for a given symbolic
sequence to appear in the lexicon) and lexical density (the extent to which other words can
be obtained from a target word by changing, deleting or inserting one or more symbols
in the target). The two measures are highly correlated and thus easy to be confounded in
measuring their effects in lexical tasks. In this paper, we propose a computational model
of lexical organisation, based on Self–Organising Maps with Hebbian connections defined
over a temporal layer (TSOMs), providing a principled algorithmic account of effects of
lexical acquisition, processing and access, to further investigate these issues. In particular,
we show that (morpho–)phonotactic probabilities and lexical density, though correlated in
lexical organisation, can be taken to focus on different aspects of speakers’ word processing
behaviour and thus provide independent cognitive contributions to our understanding of
the principles of perception of typicality that govern lexical organisation.

 

Key words

 

lexical acquisition, word processing, frequency, mental lexicon

 

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