Abstract
A chord progression is an essential building block in music. In the field of music theory is usually assumed that these progressions influence the mood, emotion, genre or other critical aspects of the songs, and also in the perception that they will cause on the listener. Therefore, it is natural to think that musical and audio features of a track should be related to its chord progressions. Choosing carefully these progressions when it comes the time of creating a new song, is a fundamental aspect depending on the feelings we want to evoke on the listener. Also, two songs can be considered alike or classified into the same emotions or genres if they use the same chord progressions. Many music classification studies are presented nowadays, but none of them take into account chord progressions, probably due to the lack of this kind of data. In this paper, classification algorithms are used to illustrate the influence of the songs’ features when it comes to pick up chord progressions to create a new song.
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This research has been funded by the Spanish MINECO project TIN2017-87600-P.
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Rico, N., Díaz, I. (2018). Chord Progressions Selection Based on Song Audio Features. In: de Cos Juez, F., et al. Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science(), vol 10870. Springer, Cham. https://doi.org/10.1007/978-3-319-92639-1_41
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