Improving Data-driven Design and Exploration of Digital Musical Instruments

We present Gesture Mapper, an application for digital musical instrument designers to rapidly prototype mappings from performer gestures to sound synthesis parameters. Prior work [2] has shown that using interactive supervised learning to generate mappings from user-generated examples can be more efficient and effective than users writing mapping functions in code. In this work, we explore new ways to improve on data-driven design of interactive systems, specifically by proposing new mechanisms for rapid exploration and comparison of multiple alternative mappings. We present a conceptual structure for interactive mappings, a basic framework for generating mappings from more diverse types of user-specified constraints than are supported by supervised learning, and the new Gesture Mapper user interface for mapping exploration and comparison.