Bayesian Framework for Room Impulse Response Reconstruction using Explicit Frequency Regularisation

Figueroa-Duran A, Karakonstantis X, Fernandez-Grande E. Bayesian Framework for Room Impulse Response Reconstruction using Explicit Frequency Regularisation. In: Convention Paper. Audio Engineering Society; 2024. Paper 10717. Available from: https://aes.org/publications/elibrary-page/?id=22530

@inproceedings{FigueroaDuran2024_22530,
  author = {Figueroa-Duran, Antonio and Karakonstantis, Xenofon and Fernandez-Grande, Efren},
  title = {{Bayesian Framework for Room Impulse Response Reconstruction using Explicit Frequency Regularisation}},
  note = {Paper 10717},
  year = {2024},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22530}
}

TY  - CPAPER
TI  - Bayesian Framework for Room Impulse Response Reconstruction using Explicit Frequency Regularisation
AU  - Figueroa-Duran, Antonio
AU  - Karakonstantis, Xenofon
AU  - Fernandez-Grande, Efren
M1  - Paper 10717
PY  - 2024
DA  - 2024/06/06
UR  - https://aes.org/publications/elibrary-page/?id=22530
PB  - Audio Engineering Society
LA  - en
AB  - Immersive spatial audio applications require a detailed understanding of sound fields in large volumes. However, data acquisition is often a restrictive task due to the large number of measurements required. To address this, we propose a Bayesian framework for Room Impulse Response reconstruction from a set of limited measurements. This approach enables the inclusion of physically-grounded models and explicit regularisation based on generalisable room properties in the frequency domain. Evaluation via experimental measurements in a historical academic auditorium demonstrates an efficient and accurate reconstruction, indicating potential applications in navigable sound field reproduction and augmented reality spatial audio.
ER  -