Python library for loading and using the OnAir Music Dataset, inspired by sigsep-mus-db.
First download the zips of the OnAir Music Dataset, and unzip them in a common location:
$ mkdir -p ~/onair-music
$ mv ~/Downloads/OnAir-Music-Dataset-v4-*.zip ~/onair-music/
$ cd ~/onair-music
$ unzip OnAir-Music-Dataset-v4-misc.zip
$ unzip OnAir-Music-Dataset-v4-LoFi-Vol-3.zip
Install this library, set ONAIR_PATH
, and run the example script:
$ export ONAIR_PATH=~/onair-music
$ python onair_example.py --eval-dir ./eval-stems/
track: Ronin - OnAir Music
vocals
accompaniment
vocals ==> SDR: -4.647 SIR: -6.207 ISR: 0.009 SAR: -26.630
accompaniment ==> SDR: -2.666 SIR: 6.184 ISR: 0.091 SAR: -26.630
track: Set Me Free - OnAir Music
vocals
accompaniment
vocals ==> SDR: -13.816 SIR: -2.882 ISR: 0.858 SAR: -3.895
accompaniment ==> SDR: -11.614 SIR: 2.884 ISR: 3.593 SAR: -3.895
The raw stems of the OnAir Music dataset are not provided with drums/bass/vocals/mix/other stems like MUSDB18-HQ.
Instead, the onair/config.py file defines how the custom stems should be assembled into musdb targets.
Some tracks are missing due to length mismatches in the stems or inappropriate stems (e.g. bass + kick are not provided separately). Also note that some of the LoFi hiphop tracks have very faint, ambient vocal components, and not a real singer.