K.R. Tan, M.L. Villarino, C. Maderazo
Automatic music mood recognition is still a new field of research that is gaining attention in the last decade. This study created a system that predicts which of the four quadrants of the valence-arousal space the song belongs to. The system used support-vector machine (SVM) for audio features while Naïve Bayes was used for lyrical features. audio classification achieved a high accuracy for arousal while lyrics classification achieved a high accuracy for valence. © 2019 Institute of Physics Publishing. All rights reserved.
Department of Computer and Information Sciences-University of San Carlos-Talamban Campus, Cebu City, Philippines
