Tools and tutorials for the OpenMIC-2018 dataset.
This repository contains companion source code for working with the OpenMIC-2018 dataset, a collection of audio and crowd-sourced instrument labels produced in a collaboration between Spotify and New York Universiy's MARL and Center for Data Science. The cost of annotation was sponsored by Spotify, whose contributions to open-source research can be found online at the developer site, engineering blog, and public GitHub.
If you use this dataset, please cite the following work:
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. pdf
The OpenMIC-2018 dataset is made available on Zenodo. After downloading, decompress with your favorite commandline tar utility:
$ tar xvzf openmic-2018-v1.0.0.tgz -C some/dir
This will expand into some/dir/openmic-2018
, with the following structure:
openmic-2018/
acknowledgement.md
audio/
000/
000046_3840.ogg
..
..
checksums
class-map.json
license-cc-by.txt
openmic-2018-aggregated-labels.csv
openmic-2018-individual-responses.csv
openmic-2018-metadata.csv
openmic-2018.npz
partitions/
train01.txt
test01.txt
vggish/
000/
000046_3840.json
..
..
The openmic-2018.npz
is a Python-friendly composite of the vggish
features and the openmic-2018-aggregated-labels.csv
. An example of how to train and evaluate a model is provided in a tutorial notebook.
To use the provided openmic
Python library, first clone the repository and change directory into it:
$ git clone https://github.com/cosmir/openmic-2018.git
$ cd ./openmic-2018
Next, you'll want to pull down the VGGish model parameters via the following script.
$ ./scripts/download-deps.sh
Finally, you can now install the Python library, e.g. with pip
:
$ pip install .
When initially collecting data, ten audio files were corrupted due to an issue in the source FMA dataset:
'071826', '071827', '087435', '095253', '095259',
'095263', '102144', '113025', '113604', '138485'
Of the 41k responses obtained, only three resulted in erroneous labels by annotators. The following rows have been manually corrected:
Sample Key | Instrument | True Label |
---|---|---|
095253_134400 | piano | yes |
095263_96000 | mallet percussion | yes |
113025_99840 | trumpet | yes |