Liveness and machine listening in musical live coding: A conceptual framework for designing agent-based systems

Paper i proceeding, 2023

Music-making with live coding is a challenging endeavour during a performance. Contrary to traditional music performances, a live coder can be uncertain about how the next code evaluation will sound. Interactive artificial intelligence (AI) offers numerous techniques for generating future outcomes. These can be implemented on both the level of the liveness of the code and also on the generated musical sounds. I first examine the structural characteristics of various live coding systems that use agent-based technologies and present a high-level diagrammatic representation. I sketch simple block diagrams that enable me to construct a conceptual framework for designing agent-based systems. My aim is to provide a practical framework to be used by practitioners. This study has two parts: i) a high-level diagrammatic representation informed by previous studies, where I analyze patterns of interaction in eight live coding systems, and ii) a conceptual framework for designing agent-based performance systems by combining both liveness and machine listening. I identify diverse patterns of interactivities between the written code and the generated music, and I draw attention to future perspectives. One code snippet for SuperCollider is provided and mapped to the conceptual framework. The vision of the study is to raise awareness on interactive AI systems within the community and potentially help newcomers navigating in the vast potential of live coding.