Acquisition of uniform impression of music using graph kernel filter

Abstract

The impression of songs varies from person to person. Sensitivity depending on this individual is greatly different between individuals and quantification is difficult. In addition, since sensitivity changes with time, fixed point observation is also necessary and takes time. In this case, focusing on the graph Laplacian which has the property of Fourier transform among the deep learning attracting attention in recent years, we clarify the trend of the frequency characteristic which affects the experiment time by computer experiments and the sensitivity of music.