Algorithmic Methods for Calibrating Material Absorption Within Geometric Acoustic Modeling

Deetz N, Boren B. Algorithmic Methods for Calibrating Material Absorption Within Geometric Acoustic Modeling. In: AES Convention 153. Audio Engineering Society; 2022. Paper 11. Available from: https://aes.org/publications/elibrary-page/?id=21891

@inproceedings{Deetz2022_21891,
  author = {Deetz, Noah and Boren, Braxton},
  title = {{Algorithmic Methods for Calibrating Material Absorption Within Geometric Acoustic Modeling}},
  booktitle = {AES Convention 153},
  note = {Paper 11},
  year = {2022},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=21891}
}

TY  - CPAPER
TI  - Algorithmic Methods for Calibrating Material Absorption Within Geometric Acoustic Modeling
AU  - Deetz, Noah
AU  - Boren, Braxton
T2  - AES Convention 153
M1  - Paper 11
PY  - 2022
DA  - 2022/10/06
UR  - https://aes.org/publications/elibrary-page/?id=21891
PB  - Audio Engineering Society
LA  - en
AB  - In room acoustic modeling, digital geometric room models are commonly created to aid acousticians in auditioning different possible changes that could be made to a room. It is critically important to have the mathematical parameters and final auralization of the space match, so acousticians can know with confidence changes made in the simulation will translate to the room itself. Traditionally, acousticians have been required to laboriously adjust acoustic and scattering coefficients of planes in the room model in order to align various measured metrics like reverb time (T30) and speech clarity (C50) to predicted ones. This express paper presents an alternative procedure where a heuristic algorithm is used to automate the acoustic calibration process. In addition, this paper showcases how a statistical database that includes mean and standard deviation measurements for acoustic coefficients can be implemented to account for material density deviation.
ER  -