Papers › String Sound Synthesizer on GPU-accelerated Finite Difference Scheme

String Sound Synthesizer on GPU-accelerated Finite Difference Scheme

30 Nov 2023arXiv:2311.18505links table onlyarchive 2025-07-28

Jin Woo Lee, Min Jun Choi, Kyogu Lee

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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.

Code

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