Repeating Pattern Discovery from Acoustic Musical Signals

Music pieces are typically repetitive. The automatic extraction of repeating patterns is useful for music summary, indexing and retrieval. An effective approach for repeating pattern discovery is proposed. In order to represent the melody similarity more accurately, a constant Q transform is used for feature extraction and a novel similarity measure between musical features is proposed. From the self-similarity matrix of the music, an adaptive method is used to extract all the significant repeating patterns. Experiments on pop music indicate the approach is promising.