用区间段统一分析节奏数据，揭示其规律与结构。
Rhythmic segment analysis: Conceptualizing, visualizing, and measuring rhythmic data
- 将节奏数据拆分为时长与模式的区间段，构建统一分析框架。
- 提出模式-时长图和新度量方法，更精准刻画节奏非等时性。
- 适用于音乐、生物节律等领域的节奏分析，适合研究者参考。
本文提出一种分析节奏数据规律性的框架，核心是将节奏数据视为固定长度的连续间隔段，每个段可分解为时长与模式（间隔间比例）。该框架统一了三种节奏可视化方法，并引出第四种：模式-时长图。结合聚类转移网络，能直观揭示合成数据与真实世界节奏数据中的规律。同时，该框架推广了两种常见节奏度量：节奏比与归一化成对变异性指数（nPVI），并指出nPVI可重构为偏离等时性的平均距离，进而提出更通用的非等时性度量。此外，提出的“量化性”概念可能为小整数比节奏的广泛争议提供新视角。
原文摘要 · Abstract (English)
This paper develops a framework for conceptualizing, visualizing, and measuring regularities in rhythmic data. I propose to think about rhythmic data in terms of interval segments: fixed-length groups of consecutive intervals, which can be decomposed into a duration and a pattern (the ratios between the intervals). This simple conceptual framework unifies three rhythmic visualization methods and yields a fourth: the pattern-duration plot. When paired with a cluster transition network, it intuitively reveals regularities in both synthetic and real-world rhythmic data. Moreover, the framework generalizes two common measures of rhythmic structure: rhythm ratios and the normalized pairwise variability index (nPVI). In particular, nPVI can be reconstructed as the average distance from isochrony, and I propose a more general measure of anisochrony to replace it. Finally, the novel concept of quantality may shed light on wider debates regarding small-integer-ratio rhythms.
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