MusicGenreTranslation

Python code for reproducing music genre translation experiments presented in the paper Leveraging knowledge bases and parallel annotations for music genre translation at ISMIR 2019.

Organisation

• The directory "scripts" contains standalone python scripts.
• The directory "tag_translation" contains the python module used to perform tag translation.
• The directory "docker" contains the Dockerfile that defines the image in which the experiment's code can be run.

Simply reproduce the results

Make sure you have Docker installed, and run

git clone git@github.com:deezer/MusicGenreTranslation.git
cd MusicGenreTranslation
./build_and_run.sh

This will:

• build a docker image called tag_translation_research in which the experiments will be run.
• launch a container where all the scripts to produce the articles' figures will be run.
• download all the groundtruth files for train and validation data in the common recordings dataset, along with the taxonomies provided by acousticbrainz for the 3 sources lastfm, discogs and tagtraum. Additionally, a mapping between recodingmbids and artistmbids will also be downloaded. The artist information is need to perform the stratified sampling when generating folds.
• run all the necessary scripts to generate the final plots

After this, if everything went well, the figures will be in data/plots.

/!\ Because running all the results is quite long, the plots are generated only for the lowest amounts of data, but you can change that setting in tag_translation/conf.py.

Additional notes

To have better control of how the scripts are executed as well as the environment you can refer to tag_translation/conf.py.