The dataset is made available by Spotify AB under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. The full terms of this license are included alongside this dataset.

This dataset is preprocessed and compressed to 32khz mp3 files. The bytes of the mp3 files are embedded. The mp3 bytes can be decoded quickly using for example or minimp3.

Take a look at the original dataset for more information. The original dataset contains the following:

10 second snippets of audio, in a directory format like 'audio/{0:3}/{0}.ogg'.format(sample_key) VGGish features as JSON objects, in a directory format like 'vggish/{0:3}/{0}.json'.format(sample_key) MD5 checksums for each OGG and JSON file Anonymized individual responses, in 'openmic-2018-individual-responses.csv' Aggregated labels, in 'openmic-2018-aggregated-labels.csv' Track metadata, with licenses for each audio recording, in 'openmic-2018-metadata.csv' A Python-friendly NPZ file of features and labels, 'openmic-2018.npz' Sample partitions for train and test, in 'partitions/*.txt'

Homepage

https://zenodo.org/records/1432913

Citation

Humphrey, Eric J., Durand, Simon, and McFee, Brian. "OpenMIC-2018: An Open Dataset for Multiple Instrument Recognition." in Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018.

License

CC BY 4.0

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