English

SnakeSynth: New Interactions for Generative Audio Synthesis

Human-Computer Interaction 2023-07-13 v1 Sound Audio and Speech Processing

Abstract

I present "SnakeSynth," a web-based lightweight audio synthesizer that combines audio generated by a deep generative model and real-time continuous two-dimensional (2D) input to create and control variable-length generative sounds through 2D interaction gestures. Interaction gestures are touch and mobile-compatible with analogies to strummed, bowed, and plucked musical instrument controls. Point-and-click and drag-and-drop gestures directly control audio playback length and I show that sound length and intensity are modulated by interactions with a programmable 2D coordinate grid. Leveraging the speed and ubiquity of browser-based audio and hardware acceleration in Google's TensorFlow.js we generate time-varying high-fidelity sounds with real-time interactivity. SnakeSynth adaptively reproduces and interpolates between sounds encountered during model training, notably without long training times, and I briefly discuss possible futures for deep generative models as an interactive paradigm for musical expression.

Keywords

Cite

@article{arxiv.2307.05830,
  title  = {SnakeSynth: New Interactions for Generative Audio Synthesis},
  author = {Eric Easthope},
  journal= {arXiv preprint arXiv:2307.05830},
  year   = {2023}
}
R2 v1 2026-06-28T11:27:59.530Z