Abstract
This study analyzes music using a stochastic process, particularly, the Vasicek model. This approach interprets note progression in a song as a mean-reverting process, allowing the estimation of three parameters such as the speed of the revision to the mean, long-term level of the mean, and volatility. In addition, the entropy is evaluated for each song to identify the randomness of rise–fall patterns for each music genre. Our results characterize certain types of music and could be used to create new indicators for music classification.
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