Datasets › https://github.com/Computational-Cognitive-Musicology-Lab/CoCoPops
https://github.com/Computational-Cognitive-Musicology-Lab/CoCoPops (CoCoPops: The Coordinated Corpus of Popular Musics)
CoCoPops is a meta-corpus of melodic and harmonic transcriptions of popular music. CoCoPops has been developed primarily by Nat Condit-Schultz and Claire Arthur in the Computational and Cognitive Musicology Lab, within the Georgia Tech Center for Music Technology. The goal of CoCoPops is to make a large ammount of comparable melodic/harmonic data available in a consistent, standardized format. All CoCoPops files are stored in humdrum format. CoCoPops currently includes of two main sub-corpora, the Billboard subset and the Rolling Stone subset. We plan on continuing to add more as additional datasets and corpora of popular music with melodic transcriptions become available.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
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License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- https://github.com/Computational-Cognitive-Musicology-Lab/CoCoPops
1 variant name, as the archive lists them.
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