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arXiv · 2311.18505

String Sound Synthesizer on GPU-accelerated Finite Difference Scheme

Jin Woo Lee·Min Jun Choi·Kyogu Lee
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Abstract

This paper introduces a nonlinear string sound synthesizer, based on a finite difference simulation of the dynamic behavior of strings under various excitations. The presented synthesizer features a versatile string simulation engine capable of stochastic parameterization, encompassing fundamental frequency modulation, stiffness, tension, frequency-dependent loss, and excitation control. This open-source physical model simulator not only benefits the audio signal processing community but also contributes to the burgeoning field of neural network-based audio synthesis by serving as a novel dataset construction tool. Implemented in PyTorch, this synthesizer offers flexibility, facilitating both CPU and GPU utilization, thereby enhancing its applicability as a simulator. GPU utilization expedites computation by parallelizing operations across spatial and batch dimensions, further enhancing its utility as a data generator.

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BibTeXRIS

Jin Woo Lee, Min Jun Choi, Kyogu Lee. 2023-11-30. String Sound Synthesizer on GPU-accelerated Finite Difference Scheme. https://arxiv.org/abs/2311.18505

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