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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.

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