Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music

Chiu CY, Müller M, Davies ME, Su AWY, Yang YH (2023)

Publication Type: Journal article

Publication year: 2023

Journal

IEEE/ACM Transactions on Audio, Speech and Language Processing Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 31

Pages Range: 2824-2835

DOI: 10.1109/TASLP.2023.3297956

Abstract

To model the periodicity of beats, state-of-the-art beat tracking systems use 'post-processing trackers' (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For expressive classical music, however, these assumptions can be too rigid. With two large datasets of Western classical piano music, namely the Aligned Scores and Performances (ASAP) dataset and a dataset of Chopin's Mazurkas (Maz-5), we report on experiments showing the failure of existing PPTs to cope with local tempo changes, thus calling for new methods. In this paper, we propose a new local periodicity-based PPT, called predominant local pulse-based dynamic programming (PLPDP) tracking, that allows for more flexible tempo transitions. Specifically, the new PPT incorporates a method called 'predominant local pulses' (PLP) in combination with a dynamic programming (DP) component to jointly consider the locally detected periodicity and beat activation strength at each time instant. Accordingly, PLPDP accounts for the local periodicity, rather than relying on a global tempo assumption. Compared to existing PPTs, PLPDP particularly enhances the recall values at the cost of a lower precision, resulting in an overall improvement of F1-score for beat tracking in ASAP (from 0.473 to 0.493) and Maz-5 (from 0.595 to 0.838).

Authors with CRIS profile

Meinard Müller Lehrstuhl für Semantische Audiosignalverarbeitung (AudioLabs)

Involved external institutions

National Cheng Kung University TW Taiwan (TW) Universidade de Coimbra PT Portugal (PT) Taiwan AI Labs TW Taiwan (TW)

How to cite

APA:

Chiu, C.Y., Müller, M., Davies, M.E., Su, A.W.Y., & Yang, Y.H. (2023). Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music. IEEE/ACM Transactions on Audio, Speech and Language Processing, 31, 2824-2835. https://dx.doi.org/10.1109/TASLP.2023.3297956

MLA:

Chiu, Ching Yu, et al. "Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music." IEEE/ACM Transactions on Audio, Speech and Language Processing 31 (2023): 2824-2835.

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