#4175. A multi-genre model for music emotion recognition using linear regressors

August 2026publication date
Proposal available till 17-05-2025
4 total number of authors per manuscript6020 $

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Journal’s subject area:
Visual Arts and Performing Arts;
Music;
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Abstract:
Making the link between human emotion and music is challenging. Our aim was to produce an efficient system that emotionally rates songs from multiple genres. To achieve this, we employed a series of online self-report studies, utilising Russells circumplex model. The first study (n = 44) identified audio features that map to arousal and valence for 20 songs. From this, we constructed a set of linear regressors. The second study (n = 158) measured the efficacy of our system, utilising 40 new songs to create a ground truth. Results show our approach may be effective at emotionally rating music, particularly in the prediction of valence.
Keywords:
Arousal; emotion; MER; music; perception; regression; valence

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