Machine Learning for Music Information Retrieval

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