2003/03/24 by Rudi Cilibrasi, Cilibrasi, Rudi, Paul Vitányi +3
Computer Science · #Data Analysis #E.4 #F.1.3 #FOS: Computer and information sciences #FOS: Physical sciences #H.3.1 #I.5.3 #J.5 #Machine Learning (cs.LG) #Music and Audio Processing #Neural Networks and Applications #Sound (cs.SD) #Statistics and Probability (physics.data-an) #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.cs/0303025
openalex publication_date 2003/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a fully automatic method for music classification, based only on compression of strings that represent the music pieces. The method uses no background knowledge about music whatsoever: it is completely general and can, without change, be used in different areas like linguistic classification and genomics. It is based on an ideal theory of the information content in individual objects (Kolmogorov complexity), information distance, and a universal similarity metric. Experiments show that the method distinguishes reasonably well between various musical genres and can even cluster pieces by composer.