AIcrowd | WWW 2018 Challenge: Learning to Recognize Musical Genre

The following rules have to be observed by all participants:

Participants are allowed at most 5 submissions per day.
Participants are welcome to form teams. Teams should submit their predictions under a single account. The submitted paper will mention all members.
Participants have to release their solution under an Open Source License of their choice to be eligible for prizes. We encourage all participants to open-source their code!
While submissions by Admins and Organizers can serve as baselines, they won’t be considered in the final leaderboard.
Training must be done with the audio from the FMA medium subset only. In particular, the large and full subsets must not be used. Neither should fma_features.csv (from fma_metadata.zip), which was computed on the full set.
Metadata, e.g. the song title or artist name, cannot be used for the prediction. The submitted algorithms shall learn to map an audio signal, i.e. a time series, to one of the 16 target genres. In particular, no information (audio features or metadata) from external websites or APIs can be used. This will be enforced in the second round, when the submitted systems will only have access to a set of mp3s to make predictions.
In case of conflicts, the decision of the Organizers will be final and binding.
Organizers reserve the right to make changes to the rules and timeline.
Violation of the rules or other unfair activity may result in disqualification.

For the second round, the docker containers will have access to the following resources with a timeout of 10 hours :

Guidelines for packaging the code, and submitting your models for Round-2 are now available at :

Challenge Rules