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Research into music genre classification using metaheuristic algorithms. Submitted as my final Technical Project as part of the Tonmeister degree (BSc) at the University of Surrey

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MusicGenreClassification

Researched the use of metaphor-based metaheuristic feature selection algorithms in music genre classification. Experiments were ran comparing:

  • PCA
  • ReliefF-SFS
  • Self Adaptive Harmony Search (SAHS)
  • Binary Cuckoo Search (BCS)
  • Binary Dragonfly Algorithm (BDFA)

SAHS, BCS and BDFA were then used to build features sets for binary classifiers e.g. rock vs pop, reggage vs classical.

Rhythm patterns extracted using https://github.com/tuwien-musicir/rp_extract

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Research into music genre classification using metaheuristic algorithms. Submitted as my final Technical Project as part of the Tonmeister degree (BSc) at the University of Surrey

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