LYRIC-BASED SONG EMOTION DETECTION WITH AFFECTIVE LEXICON AND FUZZY CLUSTERING METHOD

A method is proposed for detecting the emotions of Chinese song lyrics based on an affective lexicon. The lexicon is composed of words translated from ANEW and words selected by other means. For each lyric sentence, emotion units, each based on an emotion word in the lexicon, are found out, and the influences of modifiers and tenses on emotion units are taken into consideration. The emotion of a sentence is calculated from its emotion units. To figure out the prominent emotions of a lyric, a fuzzy clustering method is used to group the lyric’s sentences according to their emotions. The emotion of a cluster is worked out from that of its sentences considering the individual weight of each sentence. Clusters are weighted according to the weights and confidences of their sentences and singing speeds of sentences are considered as the adjustment of the weights of clusters. Finally, the emotion of the cluster with the highest weight is selected from the prominent emotions as the main emotion of the lyric. The performance of our approach is evaluated through an experiment of emotion classification of 500 Chinese song lyrics.