Abstract
Existing research on music emotion classification has used the mp3 files’ meta-information and meaning of lyrics or users’ feedback description to classify the music emotion after hearing the music. In this paper, we propose the new method that classifying the music emotion by extracting chords and using Beats per Minute information of digital music. Firstly, get the valence value by the used chords, and get the arousal value by using Beat per Minute information and the extract the emotion of the music by mapping such values with Russell’s emotion model.
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Park, Sy., Sim, Hm., Kwon, Mk., Lee, Wh. (2011). Automatic Music Emotion Classification Using Chords and BPM. In: Park, J.J., Yang, L.T., Lee, C. (eds) Future Information Technology. Communications in Computer and Information Science, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22309-9_42
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DOI: https://doi.org/10.1007/978-3-642-22309-9_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22308-2
Online ISBN: 978-3-642-22309-9
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