Music genre classification is a fundamental and versatile application in many various domains. Some possible use cases for music genre classification include:
- music recommendation systems;
- content organization and discovery;
- radio broadcasting and programming;
- music licensing and copyright management;
- music analysis and research;
- content tagging and metadata enrichment;
- audio identification and copyright protection;
- music production and creativity;
- healthcare and therapy;
- entertainment and gaming.
The model is trained based on publicly available dataset of labeled music data — GTZAN Dataset — that contains 1000 sample 30-second audio files evenly split among 10 genres:
- blues;
- classical;
- country;
- disco;
- hip-hop;
- jazz;
- metal;
- pop;
- reggae;
- rock.
The final code is available as a Kaggle notebook. See also my Medium article for more details.
- Downloads last month
- 266
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.