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SnakeSynth: New Interactions for Generative Audio Synthesis

2023/07/11 by Easthope, Eric · 1 citation
#Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Human-Computer Interaction (cs.HC) #Sound (cs.SD) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2307.05830

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.

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