Generative Sonification of Synthetic Virology Data with Waveshaping and Granular Synthesis Techniques

Abstract As the field of ubiquitous music has matured and developed since its inception, it has turned its attention to the question of sonification and how sonification techniques might be used to create music from the many rich sources of data that both mediate and permeate our day-to-day lives. The system presented in this paper focuses on the sonification of synthetic virology data. The authors outline an approach to sonification that integrates agent-based modeling for music generation with waveshaping and granular synthesis techniques to render key components of a viral dataset in musical terms.