Getting Started

Computational Music Analysis, CU–Boulder, May 2016

bio picture of Kris Shaffer, Ph.D.Welcome to Computational Music Analysis, a joint offering of the Department of Music Theory and the Department of Computer Science at CU–Boulder! I’m excited about working with you all these next three weeks to explore computational musicology and uncover some new insights about music together.

We meet every morning at 9am in Imig Music, room N1B49 (also known as CAML II). It’s kind of hard to find if you’re unfamiliar with the College of Music. Go in the main entrance, turn left (North), go down the stairs when you reach them, turn left again, and go all the way to the end of the hall. DO NOT TURN RIGHT to follow the hall. Instead, turn left, and that’s our room (right next to the mens room and across from CAML I). I’ll try to be around early and in the hall to help those who may be lost find the room.

There are a few things you need to know about the class.

First, this course is interdisciplinary. That means we’ll have students in the class who are experts in music, others who are experts in computer science and/or engineering, and still others who have substantial experience with both. If you’re joining the class with little-to-no musical background, that’s absolutely fine (as long as you know how to code or do things responsibly with numbers). If you know nothing about writing code, that’s also fine (as long as you know your music theory). We’ll be doing research that needs expertise from all of these disciplines — music theory, computer science, and statistics. To do this research, we’ll need expertise that likely transcends what a single mind can handle at once. Putting together our various experience and knowledge bases, we’ll be able to accomplish a lot more than any of us as individuals, especially on this time scale. In fact, we’ll likely be able to do a dissertation’s worth of work in less than two weeks, discovering a lot of cool things, as well as building our understanding of areas other than our primary field. We’ll also build skills in interdisciplinary collaboration that many employers are seeking — both in engineering and in music, and especially in the interdisciplinary field of data science.

Second, the course is vertically integrated. That means that undergraduate students, graduate students, and faculty (i.e., me) will be working together on our research. Educational research shows that there are substantial benefits to having people at different levels of skill working together — both learning from and teaching peers helps us pick up and solidify new skills. Further, life outside of school rarely involves people working together on a project who are at the exact same level of development in the exact same field of study. Thus, working productively with team members at different stages (as well as in different fields) will be another valuable experience to add to your résumé and make use of in your professional life after/outside of CU.

Finally, though this course is data-heavy and offered by two professional schools — Music and Engineering/Applied Science — this course is humanistic. In other words, in the spirit of the humanities, we always want to be asking why? and what does it mean? We won’t just work through new ways to crunch numbers and mine data. We’ll be working on developing the skills of thinking critically and creatively about data mining and data analysis, and applying what we find to our understanding of music as a human cultural practice, grounded in history. There may be commercial and financial implications to what we do, and to the skills we develop, but we will always do our best to interrogate our methods and findings critically and ask the deeper questions about what it means.

I hope you are as excited about this course as I am! This is my favorite course to teach, and it will be my last time teaching it at CU before I move away from Boulder this summer, so I’m really looking forward to our time together. See you all soon!

– Kris Shaffer, Ph.D.
(for those of you who don’t know me already, I prefer to be called Kris)

P.S. Feel free to browse the whole course website if you like, including the syllabus and assignment guide. We will also look at those together later this week.