Designing Percussive Timbre Remappings: Negotiating Audio Representations and Evolving Parameter Spaces

Timbre remapping is an approach to audio-to-synthesizer parameter mapping that aims to transfer timbral expressions from a source instrument onto synthesizer controls. This process is complicated by the ill-defined nature of timbre and the complex relationship between synthesizer parameters and their sonic output. In this work, we focus on real-time timbre remapping with percussion instruments, combining technical development with practice-based methods to address these challenges. As a technical contribution, we introduce a genetic algorithm - applicable to black-box synthesizers including VSTs and modular synthesizers - to generate datasets of synthesizer presets that vary according to target timbres. Additionally, we propose a neural network-based approach to predict control features from short onset windows, enabling low-latency performance and feature-based control. Our technical development is grounded in musical practice, demonstrating how iterative and collaborative processes can yield insights into open-ended challenges in DMI design. Experiments on various audio representations uncover meaningful insights into timbre remapping by coupling data-driven design with practice-based reflection. This work is accompanied by an annotated portfolio, presenting a series of musical performances and experiments with reflections.