Mood is an important attribute of music, and knowledge on mood can be used as a basic ingredient in music recommender and retrieval systems. Moods are assumed to be dominantly determined by two dimensions: valence and arousal. An experiment was conducted to attain data for song-based ratings of valence and arousal. It is shown that subject-averaged valence and arousal can be predicted from music features by a linear model.
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