Spatial Estimation of Room Acoustic Parameters from Sound Field Reconstruction Methods

Figueroa-Duran A, Fernandez-Grande E. Spatial Estimation of Room Acoustic Parameters from Sound Field Reconstruction Methods. In: Convention Paper. Audio Engineering Society; 2026. Paper 10309. Available from: https://aes.org/publications/elibrary-page/?id=23201

@inproceedings{FigueroaDuran2026_23201,
  author = {Figueroa-Duran, Antonio and Fernandez-Grande, Efren},
  title = {{Spatial Estimation of Room Acoustic Parameters from Sound Field Reconstruction Methods}},
  note = {Paper 10309},
  year = {2026},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=23201}
}

TY  - CPAPER
TI  - Spatial Estimation of Room Acoustic Parameters from Sound Field Reconstruction Methods
AU  - Figueroa-Duran, Antonio
AU  - Fernandez-Grande, Efren
M1  - Paper 10309
PY  - 2026
DA  - 2026/05/28
UR  - https://aes.org/publications/elibrary-page/?id=23201
PB  - Audio Engineering Society
LA  - en
AB  - Room acoustic parameters are crucial for characterising the acoustic behaviour of indoor spaces. While global metrics provide convenient descriptors of a rooms overall behaviour, a more spatially detailed analysis offers deeper insight into the spatial distribution of the sound field properties, albeit at a higher experimental cost. This paper proposes a methodology that leverages the predictive capabilities of sound field reconstruction methods to estimate room acoustic parameters as a function of position. The approach is experimentally evaluated in an auditorium, where it achieves accurate estimation of temporal and energetic room acoustic parameters across the entire audience area based on a sparse set of observations. In addition, the reconstructed field yields higher intelligibility indices compared to the raw measurements. Overall, these results highlight the potential of sound field reconstruction techniques as a practical tool for room acoustic characterisation and for supporting assistive listening technologies.
ER  -