This course presents a thorough introduction to the research domain of music informatics. This has many commercial and public applications, from music streaming and recommendation, to archiving and music creation. Through lectures, labs and a project, the student will obtain an overview of music informatics, its history and applications as well as a review of basic principles of signal processing and machine learning. The student will learn how music content at different levels of abstraction can be expressed and compared with distinctive features; ways to model music data by means of machine learning methods; and how to evaluate models of music data in the lab and in real life.

Required text: M. Müller Fundamentals of music processing : using Python and Jupyter notebooks 2021.

Python notebooks: https://www.audiolabs-erlangen.de/resources/MIR/FMP/C0/C0.html

Please read "AI-Native PhD Students", specifically the TL;DR

Teaching assistants:

"Berta Jansat Ballarín" <bertajb@kth.se>

"Filip Danielsson" <fidani@kth.se>