Downbeat Tracking

GuitarSet is a dataset of high-quality guitar recordings and rich annotations. It contains 360 excerpts 30 seconds in length. The 360 excerpts are the result of the following combinations: * 6 players, * 2 versions: comping and soloing, * 5 styles: Rock, Singer-Songwriter, Bossa Nova, Jazz, and Funk, * 3 progressions: 12 Bar Blues, Autumn Leaves, and Pachelbel Canon, * 2 tempi: slow and fast. Each excerpt is annotated with 6 pitch contour and midi note annotations (one per string), 2 chord annotations (instructed and performed), beat and tempo annotations. Source: https://guitarset.weebly.com/ Audio Source: https://zenodo.org/record/3371780

The Groove MIDI Dataset (GMD) is composed of 13.6 hours of aligned MIDI and (synthesized) audio of human-performed, tempo-aligned expressive drumming. The dataset contains 1,150 MIDI files and over 22,000 measures of drumming.

The gtzan8 audio dataset contains 1000 tracks of 30 second length. There are 10 genres, each containing 100 tracks which are all 22050Hz Mono 16-bit audio files in .wav format. The genres are: - blues - classical - country - disco - hiphop - jazz - metal - pop - reggae - rock

ASAP is a dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music. The scores are provided as paired MusicXML files and quantized MIDI files, and the performances as paired MIDI files and partially as audio recordings. Scores and performances are aligned with downbeat, beat, time signature, and key signature annotations. Source: ASAP: a dataset of aligned scores and performances for piano transcription

This data set includes beat and bar annotations of the ballroom dataset, introduced by Gouyon et al. [1]. [1] Gouyon F., A. Klapuri, S. Dixon, M. Alonso, G. Tzanetakis, C. Uhle, and P. Cano. An experimental comparison of audio tempo induction algorithms. Transactions on Audio, Speech and Language Processing 14(5), pp.1832-1844, 2006.

This dataset includes the beat and downbeat annotations for Beatles albums. The annotations are provided by M. E. P. Davies et. al [1]. M. E. P. Davies, N. Degara, and M. D. Plumbley, “Evaluation methods for musical audio beat tracking algorithms,” in Technical Report C4DM-TR-09-06, Centre for Digital Music, Queen Mary University of London, 2009.

35 recordings of Candombe music with beat and downbeat annotations.

48 multitrack jazz recordings with many annotations.

S. W. Hainsworth and M. D. Macleod, “Particle filtering applied to musical tempo tracking,” EURASIP Journal on Advances in Signal Processing, vol. 2004, pp. 1–11, 2004

Beats, downbeats, and functional structural annotations for 912 Pop tracks. Nieto, O., McCallum, M., Davies., M., Robertson, A., Stark, A., Egozy, E., The Harmonix Set: Beats, Downbeats, and Functional Segment Annotations of Western Popular Music, Proc. of the 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, The Netherlands, 2019

J. Hockman, M. E. Davies, and I. Fujinaga, “One in the jungle: Downbeat detection in hardcore, jungle, and drum and bass.” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), 2012.

Eremenko, E. Demirel, B. Bozkurt, and X. Serra, “Audio-aligned jazz harmony dataset for automatic chord transcription and corpus-based research,” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), 2018

J. Driedger, H. Schreiber, W. B. de Haas, and M. Müller, “Towards automatically correcting tapped beat annotations for music recordings.” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), 2019