Introduction
In this course we will survey the fundamentals of, and then current research in, a broad range of work in ‘music informatics’. As with other ‘proseminar’ courses, your primary tasks are to:
- Find, assimilate, and present an overview of relevant literature;
- Write up your work as an ‘hausarbeit’ essay of 12–15 pages.
For the presentation you will work in a team, usually of 2–4 members, coordinating both the literature review and presentation of the topic at hand. A typical session will see one such team present for c.60 minutes in total, followed by 30 minutes of discussion. All members of the course are expected to participate actively (and respectfully) in each discussion session. Members may be invited to present more than once depending on numbers and subject matters (for instance, on a ‘fundamentals’ topic near the start and a ‘research’ topic later on).
For the essay you will work individually, writing up your part of the topic (or on another topic by prior agreement). Full details of deadlines, expected length and more are as published centrally:
https://www.uni-saarland.de/fachrichtung/musikwissenschaft/studium/orga/hausarbeiten.html
Topics, Schedule, Assumed Knowledge
‘Music informatics’ covers a very broad range of approaches unifying by the use of data-driven, computational methods in the pursuit of new musical understanding. The scheduled list of topics sets out a preliminary set of subject matters which we may wish to cover. However, this list is far from exhaustive of potential subjects, and nor is it fixed. In assigning student presenters to topics, we will also continually review that subject list. The course is flexible enough to accommodate the interests of those participating and we will discuss possible alternative topics as we go. In short, you will be welcome to explore interests at a level appropriate to your expertise.
Speaking of experience, this course assumes an intermediate level of fluency with music theory and analysis (chords, keys, scores, tempo and the list). This means that the music ideas serve as a familiar benchmark for exploring the computational side. Prior experience with coding, data science, and advanced mathematics is welcome but not required.
Textbooks
Assuming we follow the course schedule as set out, we will follow two ‘textbooks’ (both free and online) for the first two parts of the course on symbolic and audio-based music processing respectively:
- The music21 users’ guide: https://web.mit.edu/music21/doc/usersGuide/index.html
- Meinard Müller’s Fundamentals of Music Processing (Springer 2015):
https://www.audiolabs-erlangen.de/fau/professor/mueller/bookFMP
https://www.audiolabs-erlangen.de/resources/MIR/FMP/C0/C0.html
This provides a practical introduction to computational processing of music and in doing so also covers some of the wider fundamentals of:
- symbolic representations of music;
- object-oriented programming;
- possibilities and pitfalls in computational analysis.
Students will gain most from this course by reading through these chapters independently before the class, and especially by working through the exercises on their own. In the final, third part of the course, we focus entirely on recent scholarship into open problems in the field. Lists of relevant journals and other sources (including datasets) will be provided in advance of those sections. |
