We apply the minimum description length (MDL) methodology from information theory in order to select mathematical models for musical rhythm. We consider six models proposed by David Temperley and mathematically formalize them, which allows for an MDL analysis. As a consequence, we find that two of the models are not suitable to apply this methodology, as their codification strategy does not represent all possible rhythm sequences. A slight modification of Temperley's hierarchical model provides an improvement in codification performance, robust across all the four corpora considered in the experiments: three classical corpora commonly used in music studies and one of tango songs recently released. Our study confirms the usefulness of the MDL approach to solve the classical trade-off between model complexity and its ability to fit the data.

我们应用信息论中的最小描述长度（MDL）方法来选择音乐节奏的数学模型。我们考虑 David Temperley 提出的六个模型，并以数学形式将它们形式化，从而可以进行 MDL 分析。因此，我们发现其中两个模型不适合应用这种方法，因为它们的编码策略并不代表所有可能的节奏序列。对 Temperley 分层模型的轻微修改提供了编码性能的改进，在实验中考虑的所有四个语料库中都具有稳健性：音乐研究中常用的三个古典语料库和最近发布的探戈歌曲之一。我们的研究证实了 MDL 方法在解决模型复杂性与其拟合数据能力之间的经典权衡方面的有用性。