A Reactive Tabu Search Algorithm for Stimuli Generation in Psycholinguistics

TL;DR

This paper introduces a reactive tabu search algorithm that efficiently generates pseudowords for psycholinguistic experiments by handling complex linguistic constraints and variable nonword sizes.

Contribution

It presents a novel reactive tabu search method tailored for nonword generation, improving efficiency and practicality over existing approaches.

Findings

The algorithm effectively generates nonwords matching linguistic criteria.

Experimental results demonstrate the method's efficiency and practicality.

The approach outperforms traditional generation techniques.

Abstract

The generation of meaningless "words" matching certain statistical and/or linguistic criteria is frequently needed for experimental purposes in Psycholinguistics. Such stimuli receive the name of pseudowords or nonwords in the Cognitive Neuroscience literatue. The process for building nonwords sometimes has to be based on linguistic units such as syllables or morphemes, resulting in a numerical explosion of combinations when the size of the nonwords is increased. In this paper, a reactive tabu search scheme is proposed to generate nonwords of variables size. The approach builds pseudowords by using a modified Metaheuristic algorithm based on a local search procedure enhanced by a feedback-based scheme. Experimental results show that the new algorithm is a practical and effective tool for nonword generation.