Article Title：Modeling emotional content of music using system identification
Abstract：
Research was conducted to develop a methodology to model the emotional content of music as a function of time and musical features. Emotion is quantified using the dimensions valence and arousal, and system-identification techniques are used to create the models. Results demonstrate that system identification provides a means to generalize the emotional content for a genre of music. The average R-2 statistic of a valid linear model structure is 21.9% for valence and 78.4% for arousal. The proposed method of constructing models of emotional content generalizes previous time-series models and removes ambiguity from classifiers of emotion.
Keywords: appraisals; emotion; information retrieval; model; mood; music; perception; system identification
DOI: 10.1109/TSMCB.2005.862491
Source：IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Welcome to correct the error, please contact email: humanisticspider@gmail.com
