In this work, we propose a method for the controllable synthesis of real-time contact sounds using neural resonators. Previous works have used physically inspired statistical methods and physical modelling for object materials and excitation signals. Our method incorporates differentiable second-order resonators and estimates their coefficients using a neural network that is conditioned on physical parameters. This allows for interactive dynamic control and the generation of novel sounds in an intuitive manner. We demonstrate the practical implementation of our method and explore its potential creative applications.

翻译：在这项工作中，我们提出了一种利用神经谐振器实时合成可控接触声音的方法。以往的研究采用物理启发的统计方法及物理建模来处理物体材质与激励信号。我们的方法融合了可微的二阶谐振器，并通过基于物理参数条件化的神经网络估计其系数。这使得我们能够以直观的方式实现交互式动态控制并生成新颖声音。本文展示了该方法的实际实现，并探讨了其潜在的创造性应用。