Music Emotion Classification: Fuzzy K-nearest Neighbor Classifier

Abstract

Music expresses emotion. A number of audio extracted features have influence on the perceived emotional expression of music and due to the subjective nature of human perception; classification of the emotion of music is a challenging problem. Simply assigning an emotion class to a song segment in a deterministic way does not work well because not all people share the same feeling for a song. According to different approaches, we can provide the music emotion classification. In this paper, we consider a fuzzy k-nearest neighbor classifier to classify music emotion. For each music segment, this approach determines how likely the song segment belongs to an emotion class. This fuzzy classifier is adopted to provide the measurement of the emotion strength. The measurement is also found useful for tracking the variation of music emotions in a song.