Quantitative Neural Network Model of the Tip-of-the-Tongue Phenomenon Based on Synthesized Memory-Psycholinguistic-Metacognitive Approach

Abstract

A new three-stage computer artificial neural network model of the tip-of-the-tongue phenomenon is proposed. Each word’s node is build from some interconnected learned auto-associative two-layer neural networks each of which represents separate word’s semantic, lexical, or phonological components. The model synthesizes memory, psycholinguistic, and metamemory approaches, bridges speech errors and naming chronometry research traditions, and can explain quantitatively many tip-of-the-tongue effects