Generate dataset card
Browse files
README.md
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
dataset_info:
|
| 3 |
+
features:
|
| 4 |
+
- name: filename
|
| 5 |
+
dtype: string
|
| 6 |
+
- name: 'true'
|
| 7 |
+
sequence: float32
|
| 8 |
+
length: 20
|
| 9 |
+
- name: mask
|
| 10 |
+
sequence: int32
|
| 11 |
+
length: 20
|
| 12 |
+
- name: mp3_bytes
|
| 13 |
+
dtype: binary
|
| 14 |
+
splits:
|
| 15 |
+
- name: train
|
| 16 |
+
num_bytes: 1790991884
|
| 17 |
+
num_examples: 14915
|
| 18 |
+
- name: test
|
| 19 |
+
num_bytes: 611455142
|
| 20 |
+
num_examples: 5085
|
| 21 |
+
download_size: 0
|
| 22 |
+
dataset_size: 2402447026
|
| 23 |
+
configs:
|
| 24 |
+
- config_name: default
|
| 25 |
+
data_files:
|
| 26 |
+
- split: train
|
| 27 |
+
path: data/shard_train_*
|
| 28 |
+
- split: test
|
| 29 |
+
path: data/shard_test_*
|
| 30 |
+
---
|
| 31 |
+
# CPJKU/openmic
|
| 32 |
+
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.
|
| 33 |
+
|
| 34 |
+
This dataset is preprocessed and compressed to 32khz mp3 files. The bytes of the mp3 files are embedded.
|
| 35 |
+
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).
|
| 36 |
+
|
| 37 |
+
Take a look at the original dataset for more information.
|
| 38 |
+
The original dataset contains the following:
|
| 39 |
+
|
| 40 |
+
10 second snippets of audio, in a directory format like 'audio/{0:3}/{0}.ogg'.format(sample_key)
|
| 41 |
+
VGGish features as JSON objects, in a directory format like 'vggish/{0:3}/{0}.json'.format(sample_key)
|
| 42 |
+
MD5 checksums for each OGG and JSON file
|
| 43 |
+
Anonymized individual responses, in 'openmic-2018-individual-responses.csv'
|
| 44 |
+
Aggregated labels, in 'openmic-2018-aggregated-labels.csv'
|
| 45 |
+
Track metadata, with licenses for each audio recording, in 'openmic-2018-metadata.csv'
|
| 46 |
+
A Python-friendly NPZ file of features and labels, 'openmic-2018.npz'
|
| 47 |
+
Sample partitions for train and test, in 'partitions/*.txt'
|
| 48 |
+
|
| 49 |
+
|
| 50 |
+
## Homepage
|
| 51 |
+
https://zenodo.org/records/1432913
|
| 52 |
+
|
| 53 |
+
## Citation
|
| 54 |
+
```
|
| 55 |
+
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.
|
| 56 |
+
|
| 57 |
+
```
|
| 58 |
+
|
| 59 |
+
## License
|
| 60 |
+
CC BY 4.0
|