Efficient Diffraction Modeling Using Neural Networks and Infinite Impulse Response Filters

Mannall J, Savioja L, Calamia P, Mason R, De Sena E. Efficient Diffraction Modeling Using Neural Networks and Infinite Impulse Response Filters. J Audio Eng Soc. 2023;71(9):566-576. doi:10.17743/jaes.2022.0107

@article{Mannall2023_22232,
  author = {Mannall, Joshua and Savioja, Lauri and Calamia, Paul and Mason, Russell and De Sena, Enzo},
  title = {{Efficient Diffraction Modeling Using Neural Networks and Infinite Impulse Response Filters}},
  journal = {Journal of the Audio Engineering Society},
  volume = {71},
  number = {9},
  pages = {566--576},
  year = {2023},
  month = sep,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2022.0107},
  url = {https://doi.org/10.17743/jaes.2022.0107}
}

TY  - JOUR
TI  - Efficient Diffraction Modeling Using Neural Networks and Infinite Impulse Response Filters
AU  - Mannall, Joshua
AU  - Savioja, Lauri
AU  - Calamia, Paul
AU  - Mason, Russell
AU  - De Sena, Enzo
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 71
IS  - 9
SP  - 566
EP  - 576
PY  - 2023
DA  - 2023/09/06
DO  - 10.17743/jaes.2022.0107
UR  - https://doi.org/10.17743/jaes.2022.0107
PB  - Audio Engineering Society
LA  - en
AB  - Creating plausible geometric acoustic simulations in complex scenes requires the inclusion of diffraction modeling. Current real-time diffraction implementations use the Uniform Theory of Diffraction, which assumes all edges are infinitely long. The authors utilize recent advances in machine learning to create an efficient infinite impulse response model trained on data generated using the physically accurate Biot-Tolstoy-Medwin model. The authors propose an approach to data generation that allows their model to be applied to higher-order diffraction. They show that their model is able to approximate the Biot-Tolstoy-Medwin model with a mean absolute level difference of 1.0 dB for first-order diffraction while maintaining a higher computational efficiency than the current state of the art using the Uniform Theory of Diffraction.
ER  -