Perceptual Dimensions of Short Audio Clips and Corresponding Timbre Features

Abstract

This study applied a multi-dimensional scaling approach to isolating a number of perceptual dimensions from a dataset of human similarity judgements for short excerpts of recorded popular music (800ms). Two dimensions were well identified by two of the twelve timbral coefficients from the Echo Nestâ's Analyze service. One of these was also identified by MFCC features from the Queen Mary Vamp plugin set, however a third dimension could not be mapped by either feature set and may represent a musical feature other than timbre. Implications are discussed within the context of existing research into music cognition and suggestions for further research regarding individual differences in sound perception are given