Recurrent voice-leading patterns like the Mi-Re-Do compound cadence (MRDCC) rarely appear on the musical surface in complex polyphonic textures, so finding these patterns using computational methods remains a tremendous challenge. The present study extends the canonical n-gram approach by using skip-grams, which include sub-sequences in an n-gram list if their constituent members occur within a certain number of skips. We compiled four data sets of Western tonal music consisting of symbolic encodings of the notated score and a recorded performance, created a model pipeline for defining, counting, filtering, and ranking skip-grams, and ranked the position of the MRDCC in every possible model configuration. We found that the MRDCC receives a higher rank in the list when the pipeline employs 5 skips, filters the list by excluding n-gram types that do not reflect a genuine harmonic change between adjacent members, and ranks the remaining types using a statistical association measure.

像 Mi-Re-Do 复合节奏 (MRDCC) 这样的重复发声模式很少出现在音乐表面的复杂复音纹理中，因此使用计算方法找到这些模式仍然是一个巨大的挑战。本研究通过使用skip-grams扩展了规范的n -gram 方法，其中包括n 中的子序列-gram 列表，如果它们的组成成员出现在一定数量的跳过内。我们编译了四组西方调性音乐的数据集，包括记谱的符号编码和录制的演奏，创建了一个模型管道，用于定义、计数、过滤和排序跳跃语法，并在每个可能的模型中对 MRDCC 的位置进行排序配置。我们发现当管道使用 5 个跳跃时，MRDCC 在列表中获得更高的排名，通过排除不反映相邻成员之间真正和谐变化的n- gram 类型来过滤列表，并使用统计关联度量对其余类型进行排名.