Perceptual evaluation of automatically extracted musical motives
Oriol Nieto, Morwaread Mary Farbood · 2012
Motives are the shortest melodic ideas or patterns that recur in a musical piece. This paper presents an algorithm that automatically extracts motives from score-based representations of music. The method combines perceptual grouping principles with data mining techniques, using score-based representations of music as input. The algorithm is evaluated by comparing its output to the results of an experiment where participants were asked to label representative motives in six musical excerpts. The perceptual judgments were found to align well with the motives automatically extracted by the algorithm and the experimental data was further used to tune the threshold values for similarity and strength of grouping boundaries.