We studied the relationships between the acoustic fluctuation properties of music and the emotional evaluations of music as a component technology for an automated song selecting system based on instinct and human emotion. When people listen to music, they select songs reflect their own feelings at the time, and then they emotionally evaluate the song. We believe that our emotional evaluation of songs are influenced by the fluctuation properties of both the volume and pitch of songs. Thus, we focused on the fluctuation properties containing dynamic ideas concerning music, and extracted thirty six fluctuation properties concerning both the volume and pitch from each song using the Fast Fourier Transform. We also prepared a subjective evaluation experiment for plural songs using the Semantic Differential method, and obtained an emotional evaluation of the songs. Then, we studied the relationships between the extracted properties and the emotional evaluations of the songs by conducting a multiple discriminant analysis. As a result, a high percentage of the questions were answered correctly and low discriminant errors were shown, and therefore, we suggested that the fluctuation properties of the songs influenced the emotional evaluations of them. Furthermore, we confirmed the especial properties related with the emotional evaluation of the music by taking into consideration the coefficients of the liner discriminants of the canonical variates that describe the discriminant spaces.