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Sound Field Estimation Based on Physics-Constrained Kernel Interpolation Adapted to Environment
  • Juliano Ribeiro ,
  • Shoichi Koyama ,
  • Hiroshi Saruwatari
Juliano Ribeiro
The University of Tokyo

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Shoichi Koyama
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Hiroshi Saruwatari
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This manuscript was submitted to IEEE/ACM Transactions on Audio, Speech and Language Processing and is currently undergoing review. In this work, we propose a fully adaptive kernel function for interior sound field interpolation that considers both directed and residual sound fields and always satisfies the Helmholtz equation. The method accomplishes this by assigning each component a different kernel function. The directed field represents sound field components of intense directionality that are sparsely distributed, and is represented by a superposition of kernels with strong directionality. The residual field represents the lower amplitudes and has much less predictable behavior, and thus was assigned a neural network weighted kernel function. We compared the proposed kernel to competing kernel formulations in numerical simulations and in real data experiments.