Thank you for your interest in the McGill Billboard annotations! This is an unofficial GitHub repository of the McGill Billboard Project.

We proudly present to you an updated version of the McGill Billboard dataset, adding 2 major changes:

• Added the AcousticBrainz features.
• Replaced the Echonest features with the new Spotify analyses.

This original project link: https://ddmal.music.mcgill.ca/research/The_McGill_Billboard_Project_(Chord_Analysis_Dataset)/

Quoted from the official McGill Billboard website:

"In order to facilitate the best possible use of these data in the future, we have made them available legally under a CC0 license, but we ask that users follow scholarly norms in any public-facing work based on upon these data by citing the following ISMIR paper:"

• John Ashley Burgoyne, Jonathan Wild, and Ichiro Fujinaga, ‘An Expert Ground Truth Set for Audio Chord Recognition and Music Analysis’, in Proceedings of the 12th International Society for Music Information Retrieval Conference, ed. Anssi Klapuri and Colby Leider (Miami, FL, 2011), pp. 633–38 [1]; or Ashley Burgoyne’s dissertation:

• John Ashley Burgoyne, ‘Stochastic Processes and Database-Driven Musicology’ (PhD diss., McGill University, Montréal, Québec, 2012) [2].

Created by Lucas de Wolff, Jakko Vreeburg and Ruben Ahrens from the University of Amsterdam.