Detecting Emotions in Classical Music from MIDI Files

At a time when the quantity of sounds surrounding us is rapidly increasing and the access to different recordings as well as the amount of music files available on the Internet is constantly growing, the problem of building music recommendation systems including systems which can automatically detect emotions contained in music files is of great importance. In this article, a new strategy for emotion detection in classical music pieces which are in MIDI format is presented. A hierarchical model of emotions consisting of two levels, L1 and L2, is used. A collection of harmonic and rhythmic attributes extracted from music files allowed for emotion detection with an average of 83% accuracy at level L1.