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README.md

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----
-dataset_info:
-  features:
-  - name: filename
-    dtype: string
-  - name: 'true'
-    sequence: float32
-    length: 20
-  - name: mask
-    sequence: int32
-    length: 20
-  - name: mp3_bytes
-    dtype: binary
-  splits:
-  - name: train
-    num_bytes: 1790991884
-    num_examples: 14915
-  - name: test
-    num_bytes: 611455142
-    num_examples: 5085
-  download_size: 0
-  dataset_size: 2402447026
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/shard_train_*
-  - split: test
-    path: data/shard_test_*
----
-# CPJKU/openmic
-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](https://github.com/kkoutini/PaSST/blob/4519e4605989b8c2e62dccb5b928af9bf7bf8602/audioset/dataset.py#L55) or  [minimp3](https://github.com/f0k/minimp3py).
-
-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