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Machine Learning for Music Information Retrieval

University of Victoria via Kadenze


An introduction to data mining through the lens of music information retrieval. Topics explored include classification (genre, mood, instrument), multi-label classification (tagging), and regression (emotion/mood).


  • Tags
  • Emotion Recognition and Regression
    • We will learn about Regression and how it is applied in emotion/mood recognition, and other regression applications such as surrogate sensing for music instruments.
  • Discriminative Classifiers
    • Decision trees, perceptron, artificial neural networks, support vector machines will be covered in this session.
  • Genre Classification
    • This session is about methods of tag acquisition (surveys, games with a purpose), auto-tagging architectures, evaluation of auto-tagging.
  • Supervised Learning and Naive Bayes Classification
    • In this session, we will learn about the main idea of generative classifiers using probabilistic modeling, Bayes theorem, the naive bayes assumption, evaluation of classification, cross-validation.
  • Music Visualization

Taught by

George Tzanetakis


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