36. Mapping the Influence

Iannis Xenakis’s pioneering work has been extensively prolific and diverse. Exploring his compositional principles within the context of today’s computational capabilities, today’s state-of-the-art music technologies, and contemporary aesthetics may offer composers and performers the possibility to explore uncharted territories in their music creativity and music making. My latest free improvisation performances have been such kinds of explorations; they extensively rely on the use of Dynamic Stochastic Synthesis combined with real-time data feedback processes. I explore ways of influencing a Dynamic Stochastic Synthesis algorithm in SuperCollider (Gendy1) using its own audio signal. The audio signal either influences parameters of the Gendy1 Unit Generator itself or affects other parameters in the overall digital signal processing that the Gendy1 Unit Generator belongs to. To manage the contribution of the feedback in the process and to control other parameters of the stochastic distributions I use Machine Learning mapping and more specifically the program Wekinator. The combination of these processes offers a great variety of quite harsh, often unstable, and unpredictable spectra of tonal and noisy sounds that call for interaction and playfulness in the context of live improvised music. My essential argument, aside from the technical or aesthetical aspects of it, is that in my case Xenakis’s work has primarily influenced me in being musically curious, explorative, daring to try, daring to borrow processes from different practices, and daring to challenge aesthetics, concepts, techniques, and technologies.