Visualizing music and audio using self-similarity

Abstract

This paper presents a novel approach to visualizing the time structure of music and audio. The acoustic similarity between any two instants of an audio recording is displayed in a 2D representation, allowing identification of structural and rhythmic characteristics. Examples are presented for classical and popular music. Applications include content-based analysis and segmentation, as well as tempo and structure extraction.