Towards Predicting Expressed Emotion in Music from Pairwise Comparisons
نویسندگان
چکیده
We introduce five regression models for the modeling of expressed emotion in music using data obtained in a two alternative forced choice listening experiment. The predictive performance of the proposed models is compared using learning curves, showing that all models converge to produce a similar classification error. The predictive ranking of the models is compared using Kendall’s τ rank correlation coefficient which shows a difference despite similar classification error. The variation in predictions across subjects and the difference in ranking is investigated visually in the arousal-valence space and quantified using Kendall’s τ .
منابع مشابه
Predictive Modeling of Expressed Emotions in Music Using Pairwise Comparisons
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