P. Annibale et al., “The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensingand Rendering,” in Proc. AES Convention 131, Oct. 2011, Paper 8485. [Online]. Available: https://aes.org/publications/elibrary-page/?id=16011
Annibale P, Antonacci F, Bestagini P, Brutti A, Canclini A, Cristoforetti L, Filos J, Habets E, Kellerman W, Kowalczyk K, et al. The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensingand Rendering. In: AES Convention 131. Audio Engineering Society; 2011. Paper 8485. Available from: https://aes.org/publications/elibrary-page/?id=16011
@inproceedings{Annibale2011_16011,
author = {Annibale, Paolo and Antonacci, Fabio and Bestagini, Paolo and Brutti, Alessio and Canclini, Antonio and Cristoforetti, Luca and Filos, Jason and Habets, Emanuël and Kellerman, Walter and Kowalczyk, Konrad and Lombard, Anthony and Mabande, Edwin and Markovic, Dejan and Naylor, Patrick and Omologo, Maur},
title = {{The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensingand Rendering}},
booktitle = {AES Convention 131},
note = {Paper 8485},
year = {2011},
month = oct,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=16011}
}
TY - CPAPER
TI - The SCENIC Project: Space-Time Audio Processing for Environment-Aware Acoustic Sensingand Rendering
AU - Annibale, Paolo
AU - Antonacci, Fabio
AU - Bestagini, Paolo
AU - Brutti, Alessio
AU - Canclini, Antonio
AU - Cristoforetti, Luca
AU - Filos, Jason
AU - Habets, Emanuël
AU - Kellerman, Walter
AU - Kowalczyk, Konrad
AU - Lombard, Anthony
AU - Mabande, Edwin
AU - Markovic, Dejan
AU - Naylor, Patrick
AU - Omologo, Maur
T2 - AES Convention 131
M1 - Paper 8485
PY - 2011
DA - 2011/10/06
UR - https://aes.org/publications/elibrary-page/?id=16011
PB - Audio Engineering Society
LA - en
AB - SCENIC is an EC-funded project aimed at developing a harmonized corpus of methodologies for environment-aware acoustic sensing and rendering. The project focusses on space-time acoustic processing solutions that do not just accommodate the environment in the modeling process but that make the environment help towards achieving the goal at hand. The solutions developed within this project cover a wide range of applications, including acoustic self-calibration, aimed at estimating the parameters of the acoustic system; environment inference, aimed at identifying and characterizing all the relevant acoustic reflectors in the environment. The information gathered through such steps is then used to boost the performance of wavefield rendering methods as well as source localization/characterization/extraction in reverberant environments.
ER -