Automatic music mood recognition using Russell's twodimensional valence-arousal space from audio and lyrical data as classified using SVM and Na?ve Bayes

International Conference on Information Technology and Digital Applications 2018

计算机科学;无线电电子学

Tan, K.R.^1 ; Villarino, M.L.^1 ; Maderazo, C.^1

Department of Computer and Information Sciences-University of San Carlos-Talamban Campus, Cebu City, Philippines^1

关键词: Audio classification;    Audio features;    Four quadrant;    High-accuracy;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/482/1/012019/pdf
DOI  :  10.1088/1757-899X/482/1/012019

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

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.