  Music genre can be hard to describe: many factors are involved, such as
style, music technique, and historical context. Some genres even have
overlapping characteristics. Looking for a better understanding of how music
genres are related to musical harmonic structures, we gathered data about the
music chords for thousands of popular Brazilian songs. Here, 'popular' does not
only refer to the genre named MPB (Brazilian Popular Music) but to nine
different genres that were considered particular to the Brazilian case. The
main goals of the present work are to extract and engineer harmonically related
features from chords data and to use it to classify popular Brazilian music
genres towards establishing a connection between harmonic relationships and
Brazilian genres. We also emphasize the generalization of the method for
obtaining the data, allowing for the replication and direct extension of this
work. Our final model is a combination of multiple classification trees, also
known as the random forest model. We found that features extracted from
harmonic elements can satisfactorily predict music genre for the Brazilian
case, as well as features obtained from the Spotify API. The variables
considered in this work also give an intuition about how they relate to the
genres.
