Bendit_I/O: A System for Extending Mediated and Networked Performance Techniques to Circuit-Bent Devices

Circuit bending—the act of modifying a consumer device\u27s internal circuitry in search of new, previously-unintended responses—provides artists with a chance to subvert expectations for how a certain piece of hardware should be utilized, asking them to view everyday objects as complex electronic instruments. Along with the ability to create avant-garde instruments from unique and nostalgic sound sources, the practice of circuit bending serves as a methodology for exploring the histories of discarded objects through activism, democratization, and creative resurrection. While a rich history of circuit bending continues to inspire artists today, the recent advent of smart musical instruments and the growing number of hybrid tools available for creating connective musical experiences through networks asks us to reconsider the ways in which repurposed devices can continue to play a role in modern sonic art. Bendit_I/O serves as a synthesis of the technologies and aesthetics of the circuit bending and Networked Musical Performance (NMP) practices. The framework extends techniques native to the practices of telematic and network art to hacked hardware so that artists can design collaborative and mediated experiences that incorporate old devices into new realities. Consisting of user-friendly hardware and software components, Bendit_I/O aims to be an entry point for novice artists into both of the creative realms it brings together. This document presents details on the components of the Bendit_I/O framework along with an analysis of their use in three new compositions. Additional research serves to place the framework in historical context through literature reviews of previous work undertaken in the circuit bending and networked musical performance practices. Additionally, a case is made for performing hacked consumer hardware across a wireless network, emphasizing how extensions to current circuit bending and NMP practices provide the ability to probe our relationships with hardware through collaborative, mediated, and multimodal methods

Creative coding for the raspberry pi using the happybrackets platform

This workshop will introduce creative coding audio for the Raspberry Pi, using the beads platform for audio programming, and the HappyBrackets platform for inter-device communication and sensor data acquisition. We will demonstrate methods to allow each self-contained battery-powered device to acquire sensor data about its surroundings and the way it is being interacted with, as well as methods for designing systems where groups of these devices wirelessly communicate their state, allowing new interaction possibilities and approaches

Plecto: Investigating the Musical Affordances of Continuous Time Recurrent Neural Networks

"Plecto: Investigating the musical affordances of Continuous Time Recurrent Neural Networks" is a practice-based research project that investigates how continuous time recurrent neural networks (CTRNNs) can be applied to the problem of achieving gestural control in improvised electronic music. One of the challenges of improvising using computers is manipulating different compositional layers during a performance while maintaining granular and expressive control. Artists turn to concepts such as artificial life to solve this problem and pursue software agents with complex, responsive and organic qualities that lead to the perception of lifelikeness. Guided by this theme, I propose a design for a low frequency oscillator (LFO), called Plecto, for use within existing composition workflows that harnesses the idiosyncratic behaviours of CTRNNs as a gestural agent within improvised electronic music performances. CTRNNs have been used in studies of biological modelling such as animal locomotion, and also of minimally cognitive behaviours such as basic object perception. Their ability to produce lifelike abstract forms makes them well suited as a source of gestural control. Oliver Bown and Sebastian Lexer have applied CTRNNs to musical event generation, using evolutionary algorithms (EA) to search for different CTRNN behaviours. I have extended this approach, using a novelty search (NS) variant for the open-ended discovery of CTRNN configurations, each exhibiting novel behaviours that can be applied to different musical problems. Through a series of computational studies, I have explored the lifelike qualities of CTRNNs best suited for gestural control and a novelty search algorithm design for their discovery. An iterative design process was also undertaken, establishing clear design principles adopted to build a usable representation of the CTRNN algorithm within an LFO device built for the Ableton Live environment. Evaluation of the tool was conducted through a user survey and practice-based case studies that incorporate the device into my own improvised electronic music workflow as a gestural agent. The primary outcomes of this research are a suite of software that can be adopted by the broader community of practitioners and a series of compositions reflecting the impacts of the CTRNN algorithm on my creative process