A NEURAL NETWORK MODEL FOR THE SIMULATION OF WORD PRODUCTION ERRORS OF FINNISH NOUNS

Abstract

We constructed a connectionist model with multilayer perceptron networks for the simulation of word production errors in the Finnish language. Such errors occur as slips of the tongue in healthy subjects and even more often in aphasic patients suffering from brain damage. Word production errors are of theoretical interest as they open an avenue to inner workings of the language production system. Here we present our coding schemes for semantic and phoneme information of words, investigate the general properties of the model, and compare the results of the model against empirical naming error data from ten aphasic patients. The model was reasonable in simulating word production errors in this heterogeneous group of aphasic patients.