My scholarly research examines how musicians' choices shape musical performance. I also explore the ways in which music can be understood as a form of social interaction, and how it is mediated by cultural and technological forces. Areas of interest include improvisation, experimental music, virtual scores, online open-source software development communities, and electronic music. (A lot of this goes for my creative work as well.)
Much of my research is centered on the performance of twentieth-century experimental music, with a focus on improvisatory and electronic works. I am especially interested in how notation, performance practice, and technology intersect to shape musical realizations of works by composers like Pauline Oliveros, John Cage, and Earle Brown.
In this article, I use statistical methods to describe recurring tendencies in the music of the composer John Cage, whose works are often regarded as "random." In another article, I transcribe and compare three performances of the same composition by Earle Brown to better understand the role of the conductor in Brown's "open form" works.
I'm particularly interested in using computational methods to analyze experimental music. I created software that allows you to generate random and customized performances of Four2, the piece discussed in the article. You can download the latest version here as a Max patch. I've also been working on a Python toolkit called IndySim that allows you to simulate virtual performances of indeterminate works in order to analyze them.
You can also read my dissertation, which explores the limits and possibilities of performance of the music of John Cage and Earle Brown.
The topics covered in my blog often dovetail with my research interests. I'm also on Github!
Music and Coding
As an educator, I have long been interested in integrating coding and computational methods into the music classroom. I've developed a web-based resource called LINEWAVES to help instructors who would like to incorporate coding into their music classes.
LINEWAVES is an ever-growing repository of curricular modules that can easily be combined, customized, and integrated into existing lesson plans. At present, all of the modules are in Python, most are focused on the music theory curriculum in particular, and many make use of the wonderful music21 toolkit! Feel free to check it out. And if you're interested in contributing, please get in touch: drake [at] drakeandersen [dot] com.
Performance Spaces for Improvised and Notated Music. Journal of Music Theory 67/1. (forthcoming)
Open Source Performance Practice: The Laptop as an Instrument of Musical Democracy in Exploring the Performance Practices of Early and New Music. Eds. Rebecca Cypess, Estelí Gomez, and Rachael Lansang. (forthcoming)
Conducting Experiments: Sound and Conductors’ Movement in Experimental Music in Körper und Klänge in Bewegung [Bodies and Sounds in Motion]. Ed. Stephanie Schroedter. Vienna: mdwPress (forthcoming)
Hearing Epistemic Sound in Experimental (Music) Systems, 1958–1973. Journal of the Society for American Music 16/4 (in press)
Spaces for People: Technology, Improvisation, and Social Interaction in the Music of Pauline Oliveros. Organised Sound 27/2 (in press)
Earle Brown and the Minimalist Dialectic. Perspectives of New Music 59/1 (2021)
Indra: A Virtual Score Platform for Networked Musical Performance in the Proceedings of the International Conference on Technologies for Music Notation and Representation (TENOR). Eds. Gottfried, Hajdu, et al., 227–233. (2021)
Networked Open Form: Conductor-Mediated Improvisation with Indra in the Proceedings of the International Computer Music Conference, ICMC 2021.
(Per)forming Open Form: A Case Study with Earle Brown’s Novara. Music Theory Online 26/3 (2020)
“What can they have to do with one another?”: Approaches to Analysis and Performance in John Cage’s Four2. Music Theory Online 23/4 (2017)
(Most of these are also available–and likely more up to date–on my GitHub.)
Software for generating random and customized performances of John Cage's composition Four2. (Runs in Max.)
Python toolkit for Monte Carlo simulation of virtual performances of indeterminate music in order to analyze them. Works great alongside music21!
I made a handful of JSFX plug-ins for Cockos Reaper, mostly for teaching purposes. What is JSFX, you ask?
Click here to download my collection of Max abstractions (da.abstractions). Unzip and move to your patches folder, or another location recognized through the File Preferences.