A multiple feature model for musical similarity retrieval

Despite the “fuzzy” nature of musical similarity, which varies from one person to another, perceptual low level features combined with appropriate classification schemes have proven to perform satisfactorily for this task. Since a single feature only captures some selective characteristics of an audio signal, this information may, in some cases, not be sufficient to properly identify similarities between songs. This paper presents a system which combines a set of acoustic features for the task of retrieving similar sounding songs. The methodology for optimum feature selection and combination is explained, and the system’s performance is assessed by means of a subjective listening test.