Learning to Recognize Musical Genre from Audio
Micha\"el Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel, Salath\'e

TL;DR
This paper discusses a challenge on musical genre recognition from audio data, highlighting the task, challenge design, submission statistics, and results to advance research in automatic music genre classification.
Contribution
It introduces a new open-data challenge for musical genre recognition, providing insights into the task setup, data, and evaluation results.
Findings
Challenge attracted diverse submissions
Results demonstrate varying model performances
Insights into effective features for genre recognition
Abstract
We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics about the submissions, and present the results.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
- benjamin-paine/free-music-archive-fulldataset· 997 dl997 dl
- benjamin-paine/free-music-archive-smalldataset· 195 dl195 dl
- benjamin-paine/free-music-archive-mediumdataset· 109 dl109 dl
- benjamin-paine/free-music-archive-largedataset· 426 dl426 dl
- benjamin-paine/free-music-archive-commercial-16khz-fulldataset· 546 dl546 dl
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
