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).

翻译：为建模节拍的周期性，当前最先进的节拍跟踪系统采用依赖若干经验性全局速度过渡假设的"后处理跟踪器"（PPTs），这类方法对速度稳定的音乐效果良好。然而对于表现性古典音乐，这些假设可能过于僵化。通过使用两个大型西方古典钢琴音乐数据集——即对齐乐谱与演奏（ASAP）数据集和肖邦玛祖卡（Maz-5）数据集，我们报告了现有PPTs在应对局部速度变化时失效的实验结果，从而呼唤新方法。本文提出一种基于局部周期性的新型PPT，称为主导局部脉冲动态规划（PLPDP）跟踪，允许更灵活的速度过渡。具体而言，该新型PPT整合了名为"主导局部脉冲"（PLP）的方法与动态规划（DP）组件，联合考虑每个时刻的局部检测周期性和节拍激活强度。因此，PLPDP依据局部周期性而非全局速度假设进行建模。与现有PPTs相比，PLPDP以降低精确度为代价显著提升召回率，最终在ASAP数据集（F1分数从0.473提升至0.493）和Maz-5数据集（从0.595提升至0.838）上实现了节拍跟踪的总体F1分数改进。