JAZZVAR: A Dataset of Variations found within Solo Piano Performances of
  Jazz Standards for Music Overpainting
Eleanor Row Jingjing Tang George Fazekas
Jazz pianists often uniquely interpret jazz standards. Passages from these
interpretations can be viewed as sections of variation. We manually extracted
such variations from solo jazz piano performances. The JAZZVAR dataset is a
collection of 502 pairs of Variation and Original MIDI segments. Each Variation
in the dataset is accompanied by a corresponding Original segment containing
the melody and chords from the original jazz standard. Our approach differs
from many existing jazz datasets in the music information retrieval (MIR)
community, which often focus on improvisation sections within jazz
performances. In this paper, we outline the curation process for obtaining and
sorting the repertoire, the pipeline for creating the Original and Variation
pairs, and our analysis of the dataset. We also introduce a new generative
music task, Music Overpainting, and present a baseline Transformer model
trained on the JAZZVAR dataset for this task. Other potential applications of
our dataset include expressive performance analysis and performer
identification.