Information, communication and music: Recognition of musical dissonance and consonance in a simple reservoir computing system

TL;DR

This paper demonstrates that a simple reservoir computing system can classify musical intervals as consonant or dissonant, reflecting sensory dissonance curves and revealing geometric relationships between intervals.

Contribution

It introduces a single-node echo-state reservoir computing system for classifying musical intervals based on their consonant or dissonant nature, showing its effectiveness in signal classification.

Findings

Classification closely resembled sensory dissonance curves

Reservoir dynamics revealed geometric relationships between intervals

System successfully distinguished consonant from dissonant intervals

Abstract

Reservoir computing is an emerging, but very successful approach towards processing and classification of various signals. It can be described as a model of a transient computation, where influence of input changes internal dynamics of chosen computational reservoir. Trajectory of these changes represents computation performed by the system. The selection of a suitable computational substrate capable of non-linear response and rich internal dynamics ensures the implementation of simple readout protocols. Signal evolution based on the rich dynamics of the reservoir layer helps to emphasize differences between given signals thus enabling their easier classification. Here we present a simple reservoir computing system (single node echo-state machine) implemented on Multisim platform as a tool for classification of musical intervals according to their consonant or dissonant character. The result of this classification closely resembled sensory dissonance curve, with some significant differences. A deeper analysis of the received signals indicates the geometric relationships between the consonant and dissonant intervals, enabling their classification.