NEW TRENDS IN MUSICAL GENRE CLASSIFICATION USING

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by any-one. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and col-lective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pat-tern recognition techniques, but much faster for some appli-cations. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have exe-cuted an experiment using very recent hybrid feature selec-tion techniques based on OPF to speed up feature extraction process. 1