Genre classification of OPM songs through the use of musical features

• Main Authors: Deja, Jordan Aiko, Blanquera, Kim, Carabeo, Carlo Eliczar, Copiaco, Jo Rupert
• Format: text
• Published: Animo Repository 2014
• Subjects: Perceptrons; Philippines—Songs and music; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/6778
• Institution: De La Salle University

A dataset is built into a model for the classification of OPM songs into ten specific genres. Low-level musical features in the form of digital signals, like Spectral Centroid, Mel-Frequency Cepstral Coefficients among others, were collected to build the data set. A collection of 1000 songs, having 100 instances as representatives for each of the 10 genres from songs sang and composed by Filipino artists were used as data for the features in building the model. Different classifiers where employed to test and see which musical features specific for Filipino music are highlighted and can be attributed for further study. A multi-layer perceptron was selected most optimal for the model building. Additional features, genres have yet to be incorporated into the study in order to produce a set of more well-refined results.