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
Download the Dataset
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 .. ..
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.
Finally, you can now install the Python library, e.g. with
$ 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|