  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.
