On Parallel Performance Practices: Some Observations on Personalizing DMIs as Percussionists

Abstract

Digital musical instrument (DMI) design and performance is primarily practiced by those with backgrounds in music technology and human-computer interaction.Research on these topics is rarely led by performers, much less by those without backgrounds in technology. In this study, we explore DMI design and performance from the perspective of a singular community of classically-trained percussionists. We use a practiced-based methodology informed by our skillset as percussionists to study how instrumental skills and sensibilities can be incorporated into the personalization of, and performance with, DMIs. We introduced a simple and adaptable digital musical instrument, built using the Arduino Uno, that individuals (percussionists) could personalize and extend in order to improvise, compose and create music (études). Our analysis maps parallel percussion practices emerging from the resultant DMI compositions and performances by examining the functionality of each Arduino instrument through the lens of material-oriented and communication-oriented approaches to interactivity.

HandMonizer: a case study for personalized digital musical instrument design

“…While early DMI approaches were usually mostly leaded by (or with) the artists themselves [5]- [8], more recently the trend has inverted and DMI design has been usually practiced by researchers having backgrounds in human-computer interaction and/or music technology. Nowadays, far more rare are approaches where the design is led by or with performers [9]. A few works addressed this issue, such as [9] where percussionists can personalize a pre-designed adaptable DMI built through Arduino Uno, or [10], where a previously designed embedded DMI, the Noisebox [11], is redesigned through a user-driven procedure consisting of several workshops.…”

“…Nowadays, far more rare are approaches where the design is led by or with performers [9]. A few works addressed this issue, such as [9] where percussionists can personalize a pre-designed adaptable DMI built through Arduino Uno, or [10], where a previously designed embedded DMI, the Noisebox [11], is redesigned through a user-driven procedure consisting of several workshops.…”

“…ml5.js: Friendly machine learning for the Web.https://ml5js.org 8 https://learn.ml5js.org/#/reference/handpose9 This process is GPU intensive. To achieve the best performance a system with a dedicated GPU is advised.…”