Griffiths, DarrylCunningham, StuartWeinel, JonathanPicking, Richard2023-02-062023-02-062021-09-21Griffiths, D., Cunningham, S., Weinel, J., & Picking, R. (2021). A multi-genre model for music emotion recognition using linear regressors. Journal of New Music Research, 50(4), 355-372. https://doi.org/10.1080/09298215.2021.19773360929-821510.1080/09298215.2021.1977336http://hdl.handle.net/10034/627520This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of New Music Research on 21/09/2021, available online: https://doi.org/10.1080/09298215.2021.1977336Making 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.https://creativecommons.org/licenses/by-nc-nd/4.0/ArousalEmotionMERMusicPerceptionRegressionArticle1744-5027Journal of New Music Research