“Music Information Research” (MIR) is an interdisciplinary research field that concerns with the analysis, retrieval, processing, and generation of musical content or information. Researchers involved in MIR may have a background in signal processing, machine learning, information retrieval, human-computer interaction, musicology, psychoacoustics, psychology, or some combination of these.

In this course, we are mainly interested in the application of machine learning, in particular deep learning, to address music related problems. Specifically, the course is divided to two parts: analysis and generation.

The first part is about the analysis of musical audio signals, covering topics such as feature extraction and representation learning for musical audio, music audio classification, melody extraction, automatic music transcription, and musical source separation.

The second part is about the generation of musical material, including symbolic-domain MIDI or tablatures, and audio-domain music signals such as singing voices and instrumental music. This would involve deep generative models such as generative adversarial networks (GANs), variational autoencoders (VAE), Transformers, and diffusion models.

Here is a tentative schedule of the course:

W1. Introduction to the course
W2. Fundamentals & Music representation
W3. Analysis I (timbre): Automatic music classification and representation learning
(HW1: Singer classifier)
W4. Generation I: Source separation
W5. Generation II: GAN & Vocoders
W6. Generation III: Synthesis of notes and loops
(HW2: GAN-based Mel-Vocoder)
W7. Analysis II (pitch): Music transcription, Melody extraction, and Chord Recognition
W8. Generation IV: Symbolic MIDI generation
W9. Generation V: Symbolic MIDI generation: Advanced Topics
(HW3: Transformer-based pop piano MIDI generation)
W10. Generation VI: Singing voice generation
W11. Generation VII: Text-to-music generation
W12. Proposal of ideas of final projects
W13. Generation VIII: Differentiable DSP models and automatic mixing
W14. Miscellaneous Topics
W15. Break
W16. Oral presentation of final projects