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Music Genre Classification Project

Overview

Project exploring machine learning approaches for automated music genre classification using the FMA dataset and metadata.

Repository Structure

  • /code/: Python implementations for genre classification
    • BasicModels/: Baseline classification model implementations using sklearn libraries
    • Processing/: Data preparation scripts
    • CombinedFeatures/: Models using multiple feature types for experiments
    • SingleFeatures/: Single feature type experiments
    • Graphs/: Visualization generation
  • /fma_dataset/: Audio data and metadata
  • /Preliminary Results/: Performance graphs and genre mappings

Setup

  1. Download FMA dataset and verify checksums
  2. Run initialPreprocessing.py from Processing/
  3. Run any file in CombinedFeatures or SingleFeatures to generate results (install dependencies per file)

Results

  • Full experiment results: Google Sheets
  • Technical paper: PreliminaryResults/MusicGenreClassification.pdf

Contributors

  • Catherine Baker
  • Thomas Davidson