Pattern Discovery Techniques for Music Audio

Human listeners are able to recognize structure in music through the perception of repetition and other relationships within a piece of music. This work aims to automate the task of music analysis. Music is “explained” in terms of embedded relationships, especially repetition of segments or phrases. The steps in this process are the transcription of audio into a representation with a similarity or distance metric, the search for similar segments, forming clusters of similar segments, and explaining music in terms of these clusters. Several transcription methods are considered: monophonic pitch estimation, chroma (spectral) representation, and polyphonic transcription followed by harmonic analysis. Also, several algorithms that search for similar segments are described. These techniques can be used to perform an analysis of musical structure, as illustrated by examples.