A Large-Scale Evaluation of Acoustic and Subjective Music-Similarity Measures

Abstract

music similarity, acoustic measures, evaluation, ground-truth Subjective similarity between musical pieces and artists is an elusive concept, but one that must be pursued in support of applications to provide automatic organization of large music collections. In this paper, we examine both acoustic and subjective approaches for calculating similarity between artists, comparing their performance on a common database of 400 popular artists. Specifically, we evaluate acoustic techniques based on Mel-frequency cepstral coefficients and an intermediate ‘anchor space’ of genre classification, and subjective techniques which use data from The All Music Guide, from a survey, from playlists and personal collections, and from web-text mining.