The classical music “uta-sanshin” has been sung since the Ryukyu Kingdom period, and its skills commonly depend on folklore method by bush telegraph. Accordingly, there exist much sensibilities and esoteric expressions of the uta-sanshin expert in passing down the skill. Also, the decrease in number of successors accompanying aging and the difficulty in understanding the musical score are hindering the inheritance and the reconstruction of the music. In this paper, we apply the deep learning to Ryukyuan classical music and develop a system that identifies vocalism by real-time processing. The results of the evaluation, compared with the conventional method, show that the execution time is reduced to 98%, and the identification accuracy is improved by 6%.
J-STAGEがリニューアルされました! https://www.jstage.jst.go.jp/browse/-char/ja/
