Beat 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.

This dataset is a "part II" extension of the "Engineered cardiac microbundle time-lapse microscopy image dataset" and contains 808 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using FibroTUG platforms [1] ("Type2"). In "part I" extension, we include 732 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using microbundle strain gauge platforms [2] ("Type1"). Description of the data and file structure We include here 808 examples of "Type 2" tissue. We share the raw videos in ".tif" format and organize them based on: 1) platform type ("Type 2"), 2) experimental conditions under which the microbundles were grown ("condition_000", "condition_001",...), and 3) the batch of differentiated CMs ("batch_000", "batch_001",...) and is reflected in the folder naming. For practical reasons, we made sure that each zipped folder is less than 10GB in size, and as such, some folders were split into multiple ones. For example, "Type2_condition_000_batch_001_00.zip" and "Type2_condition_000_batch_001_01.zip" both correspond to data obtained for microbundles grown with "Type 2" platforms, under "condition 0" conditions, and for CMs from the same batch. Additionally, we include a metadata file ("metadata_type2.csv") that includes the "file_name", "experimental_conditions", "batch", "comments", and "included_in_plot". While "file_name", "experimental_conditions", and "batch" are straightforward to comprehend, "comments" correspond to remarks regarding running each specific example with MicroBundlePillarTrack software available on GitHub ). The "included_in_plot" column is used to indicate if the example was included (marked by "1") or not (marked by "0") in the summary output plot included in the main figure of the accompanying manuscript. We note that the keys for the number coded entries in "experimental_conditions" and "comments" are included in "Type2_experimental_conditions.pdf" and "Comments_key.pdf" files. Code/Software We publish this dataset to accompany our pillar tracking software (MicroBundlePillarTrack) published on GitHub. In fact, we have tested our pipeline on all 1540 examples included in this dataset and the Strain gauge platforms: Time-lapse microscopy dataset of engineered cardiac microbundles dataset. References [1] DePalma, S. J., Davidson, C. D., Stis, A. E., Helms, A. S., & Baker, B. M. (2021). Microenvironmental determinants of organized iPSC-cardiomyocyte tissues on synthetic fibrous matrices. Biomaterials science, 9(1), 93-107. [2] Zhang, K., Cloonan, P. E., Sundaram, S., Liu, F., Das, S. L., Ewoldt, J. K., ... & Chen, C. S. (2021). Plakophilin-2 truncating variants impair cardiac contractility by disrupting sarcomere stability and organization. Science Advances, 7(42), eabh3995.

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

F. Gouyon, “A computational approach to rhythm description — Audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing,” Ph.D. dissertation, Universitat Pompeu Fabra, 2006

A. Holzapfel, M. E. Davies, J. R. Zapata, J. L. Oliveira, and F. Gouyon, “Selective sampling for beat tracking evaluation,” Transactions on Audio, Speech, and Language Processing, vol. 20, no. 9, pp. 2539–2548, 2012

This dataset is a "part I" extension of the "Engineered cardiac microbundle time-lapse microscopy image dataset" and contains 732 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using microbundle strain gauge platforms [1] ("Type1"). In "part II" extension, we include 808 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using FibroTUG platforms [2] ("Type2"). Description of the data and file structure We include here 732 examples of "Type 1" tissue. We share the raw videos in ".tif" format and organize them based on: 1) platform type ("Type 1"), 2) experimental conditions under which the microbundles were grown ("condition_000", "condition_001",...), and 3) the batch of differentiated CMs ("batch_000", "batch_001",...) and is reflected in the folder naming. Additionally, we include a metadata file ("metadata_type1.csv") that includes the "file_name", "experimental_conditions", "batch", "comments", and "included_in_plot". While "file_name", "experimental_conditions", and "batch" are straightforward to comprehend, "comments" correspond to remarks regarding running each specific example with MicroBundlePillarTrack software available on GitHub. The "included_in_plot" column is used to indicate if the example was included (marked by "1") or not (marked by "0") in the summary output plot included in the main figure of the accompanying manuscript. We note that the keys for the number coded entries in "experimental_conditions" and "comments" are included in "Type1_experimental_conditions.pdf" and "Comments_key.pdf" files. Code/Software We publish this dataset to accompany our pillar tracking software (MicroBundlePillarTrack) published on GitHub. In fact, we have tested our pipeline on all 1540 examples included in this dataset and the FibroTUG platforms: Time-lapse microscopy dataset of engineered cardiac microbundles dataset. References [1] Zhang, K., Cloonan, P. E., Sundaram, S., Liu, F., Das, S. L., Ewoldt, J. K., ... & Chen, C. S. (2021). Plakophilin-2 truncating variants impair cardiac contractility by disrupting sarcomere stability and organization. Science Advances, 7(42), eabh3995. [2] DePalma, S. J., Davidson, C. D., Stis, A. E., Helms, A. S., & Baker, B. M. (2021). Microenvironmental determinants of organized iPSC-cardiomyocyte tissues on synthetic fibrous matrices. Biomaterials science, 9(1), 93-107.

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