CHEN, YU AN
Tatung University Department of Information Management Student
E-mail:g11012005@o365.ttu.edu.tw
HU, CHIH CHIEN
Tatung University Department of Information Management Assistant Professor
E-mail:holdenhu@gm.ttu.edu.tw
Abstract
Music aesthetics has become the core competence in education. Through music teaching practice, guiding students to understand various music genres and acquiring music knowledge is an important way of music education. This study uses a convolutional neural network (CNN) model to classify music genres, then students can acquire the characteristics and knowledge of music genres. Experimental results show that the proposed model has an accuracy rate of 87% in the classification of online music streaming platforms. Therefore, the proposed method can be integrated to a music streaming platform for music literacy education. For future research, it is suggested to improve the accuracy and efficiency of music information retrieval.
Keywords:music genre classification, convolutional neural network (CNN), music information retrieval (MIR), music literacy education