An investigation into a simulation of episodic memory for automatic speech recognition

Abstract

This paper investigates a simulation of episodic memory known in the literature as ‘MINERVA 2’. MINERVA 2 is a computational multiple-trace memory model that successfully predicts basic findings from the schema-abstraction literature. This model has been implemented and tested on a simple ASR task using vowel formant data taken from the Peterson & Barney database. Recognition results are compared to a number of state-of-the-art pattern classifiers, and it is shown that the episodic model achieves the best performance.