A. Franck and F. M. Fazi, “Comparison of Listener-Centric Sound Field Reproduction Methods in a Convex Optimization Framework,” in Proc. AES Conference: 2016 AES International Conference on Sound Field Control, Jul. 2016, Paper 4-3. [Online]. Available: https://aes.org/publications/elibrary-page/?id=18315
Franck A, Fazi FM. Comparison of Listener-Centric Sound Field Reproduction Methods in a Convex Optimization Framework. In: AES Conference: 2016 AES International Conference on Sound Field Control. Audio Engineering Society; 2016. Paper 4-3. Available from: https://aes.org/publications/elibrary-page/?id=18315
@inproceedings{Franck2016_18315,
author = {Franck, Andreas and Fazi, Filippo Maria},
title = {{Comparison of Listener-Centric Sound Field Reproduction Methods in a Convex Optimization Framework}},
booktitle = {AES Conference: 2016 AES International Conference on Sound Field Control},
note = {Paper 4-3},
year = {2016},
month = jul,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=18315}
}
TY - CPAPER
TI - Comparison of Listener-Centric Sound Field Reproduction Methods in a Convex Optimization Framework
AU - Franck, Andreas
AU - Fazi, Filippo Maria
T2 - AES Conference: 2016 AES International Conference on Sound Field Control
M1 - Paper 4-3
PY - 2016
DA - 2016/07/06
UR - https://aes.org/publications/elibrary-page/?id=18315
PB - Audio Engineering Society
LA - en
AB - Sound field control techniques aim at recreating a target sound field within a defined listening region. While this objective can generally be expressed as an optimization problem, the objective function, error norms, and additional constraints used vary widely between the different methods. In this paper, we focus on methods that describe a target sound field centered around a single point of the listening region, which includes mode matching, (higher order) Ambisonics, but also amplitude panning techniques. By expressing these methods in a common convex optimization framework, we highlight commonalities and differences between the approaches, but also the effects of additional constraints such as energy vector maximization, gain nonnegativity, and sparsity constraints. These theoretical comparisons are complemented by numerical examples.
ER -