This paper relates audio features based on fluctuation of music with sensibility evaluation about music as a component technology for an automatic song select system demanded on human sensibility evaluation. When people listen to music, they select a song considering both their own feelings at the time and sensibility evaluation about the song. We consider that sensibility evaluations of songs are influenced by the features based on fluctuation about both volume and pitch of the songs. Thus, we focus on features of fluctuation that contain a dynamic idea on music, and extract thirty six features of fluctuation about both volume and pitch from each songs using Fast Fourier Transform. On the other, we prepare a subjective experiment for plural songs using Semantic Differential method, and obtain the sensibility evaluation about each song. Then, we study the relationships between extracted features and sensibility evaluation about the songs with multiple discriminant analysis. As a result, high accurate discriminant hit-rates and low discriminant error are shown, therefore we suggest that audio features based on fluctuation of songs influence sensibility evaluation about the songs. Furthermore, we confirm the especial parameters related with sensibility evaluation about music while considering canonical variates which construct discriminant spaces.