Music emotion classification: a fuzzy approach

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. In this paper, we consider a different approach to music emotion classification. For each music segment, the approach determines how likely the song segment belongs to an emotion class. Two fuzzy classifiers are 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. Results are shown to illustrate the effectiveness of the approach. Categories and Subject Descriptors H.5.5 [Sound and Music Computing]: systems General Terms Algorithms, performance, experimentation. Keywords Music emotion strength, Fuzzy vector, Fuzzy k-NN (FKNN), Fuzzy Nearest-Mean (FNM), Model generator (MG), Emotion classifier (EC), Music emotion variation det...

• Type: Conference
• Year: 2006
• Where: MM
• Authors: Yi-Hsuan Yang, Chia Chu Liu, Homer H. Chen
• Keywords: Emotion, Emotion Class, MM 2006, Music Emotion