A Stochastic Process for Music: The Example of K-pop Music

S. Park, I. Kim, K. Ahn

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


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 languageEnglish
Article number012010
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 2022
Event2022 12th International Conference on Applied Physics and Mathematics, ICAPM 2022 - Singapore, Virtual, Singapore
Duration: 2022 Feb 182022 Feb 20

Bibliographical note

Funding Information:
This work was supported by (i) the Technology Innovation Program ATC+ (20014125, Development of Intelligent Management Solution for Nuclear Decommissioning Site Characterization) funded by the Ministry of Trade, Industry & Energy (MOTIE, Republic of Korea) and (ii) the Future-leading Research Initiative (Grant Number: 2021-22-0306) funded by Yonsei University.

Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)


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