F0 ESTIMATION USING BLIND SOURCE SEPARATION FOR ANALYZING NOH SINGING

The purpose of this study is to extract singing melody from mixed sounds related to Noh performances. Noh sounds include singing, accompaniments, and other elements. For analyzing Noh singing, we need singing solos, but they are hard to collect since there are only a few sources of solo passages. Therefore, we focus on the extraction of singing melody from mixtures of accompaniments and singing. In this paper, we demonstrate that source separation can be introduced as an efficient preprocessing step for Noh singing melody extraction. In addition, we compare melody extraction based on a convolutional neural network (CNN) approach with Melodia, a plug-in for melody extraction which is particularly accurate in the presence of music with wide fluctuations in pitch. We also demonstrate that CNN-based melody estimation can be efficiently trained using singing after source separation.