Kernel interpolation of acoustic transfer functions with adaptive kernel for directed and residual reverberations
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Abstract (arXiv)
An interpolation method for region-to-region acoustic transfer functions (ATFs) based on kernel ridge regression with an adaptive kernel is proposed. Most current ATF interpolation methods do not incorporate the acoustic properties for which measurements are performed. Our proposed method is based on a separate adaptation of directional weighting functions to directed and residual reverberations, which are used for adapting kernel functions. Thus, the proposed method can not only impose constraints on fundamental acoustic properties, but can also adapt to the acoustic environment. Numerical experimental results indicated that our proposed method outperforms the current methods in terms of interpolation accuracy, especially at high frequencies.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Mar 2023.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 1.
4 papers.
- 2023Implicit neural representation with physics-informed neural networks for the reconstruction of the early part of room impulse responsescited by 8
- 2023Reconstruction of Sound Field through Diffusion Modelscited by 8
- 2024Room Transfer Function Reconstruction Using Complex-valued Neural Networks and Irregularly Distributed Microphonescited by 1
- 2025Resounding Acoustic Fields with Reciprocitycited by 1
- 2025Resounding Acoustic Fields with Reciprocity23 Oct 2025
- 2024Room Transfer Function Reconstruction Using Complex-valued Neural Networks and Irregularly Distributed Microphones1 Feb 2024
- 2023Reconstruction of Sound Field through Diffusion Models14 Dec 2023
- 2023Implicit neural representation with physics-informed neural networks for the reconstruction of the early part of room impulse responses20 Jun 2023