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.
| Original language | English |
|---|---|
| Article number | 012010 |
| Journal | Journal of Physics: Conference Series |
| Volume | 2287 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 2022 12th International Conference on Applied Physics and Mathematics, ICAPM 2022 - Singapore, Virtual, Singapore Duration: 2022 Feb 18 → 2022 Feb 20 |
Bibliographical note
Publisher Copyright:© Published under licence by IOP Publishing Ltd.
All Science Journal Classification (ASJC) codes
- General Physics and Astronomy