An algorithm modelling the Irrelevant Sound Effect (ISE)

Abstract

Verbal short-term memory capacity is reduced significantly during certain background sounds. Remembering a series of digits is significantly impaired by speech or music with prominent staccato passages whereas, for example, music with prominent legato passages does not disturb performance in comparison to silence. This so-called Irrelevant Sound Effect (ISE) occurs although the background sounds are irrelevant with respect to the digit sequences to be remembered. Until now, a multitude of cognitive psychological experiments explored the ISE and collected behavioral performance data during different sound conditions. The talk presents an algorithm which models performance data in ISE experiments, i.e. the detrimental impact of background sounds on memory performance. The data base of this algorithm is about 50 background sounds and corresponding performance data, which have been collected in cognitive psychological experiments at the KU Eichstaett-Ingolstadt. The algorithm is based on the instrumental measuring of the hearing sensation fluctuation strength and is able to reconstruct the performance results in about 90% of cases within the interquartile ranges. The algorithm will be discussed within the scope of cognitive short-term memory models, which claim to explain the ISE and with respect to practical implications.