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- W3201298926 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 Russell's 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." @default.
- W3201298926 created "2021-09-27" @default.
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- W3201298926 date "2021-08-08" @default.
- W3201298926 modified "2023-10-12" @default.
- W3201298926 title "A multi-genre model for music emotion recognition using linear regressors" @default.
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- W3201298926 doi "https://doi.org/10.1080/09298215.2021.1977336" @default.
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