Abstract
In this chapter, emotion detection in classical music pieces in MIDI format is presented. A hierarchical categorical model of emotions consisting of two levels, L1 and L2, was used. A collection of harmony and rhythm MIDI features extracted from music files allowed for emotion detection with an average of 82% accuracy at level L1. We propose hierarchical emotion detection analogous to the used hierarchical model of emotions with categories at two levels, L1 and L2. We present a method for tracking changing emotions during the course of a musical piece. The collected data enabled determining the dominant emotion in the musical compositions, presenting emotion histograms, and constructing maps visualizing the distribution of emotions over time. The amount of changes of emotions during a piece may be different; therefore, we introduced a parameter evaluating the quantity of changes of emotions in a musical composition.
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