English phonotactic learning is modeled by means of the PHACTS algorithm, a topological neuronal receptive field implementing a phonotactic activation function aimed at capturing both local (i.e., phonemic) and global (i.e., word-level) similarities among strings. The limits and merits of the model are presented.

PHACTS about activation-based word similarity effects

Celata C
2012-01-01

Abstract

English phonotactic learning is modeled by means of the PHACTS algorithm, a topological neuronal receptive field implementing a phonotactic activation function aimed at capturing both local (i.e., phonemic) and global (i.e., word-level) similarities among strings. The limits and merits of the model are presented.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2679397
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