Supplementary data for: A Low-Dimensional Projection of Sound Absorption Coefficients for a Scattering Delay Network Reverberator

Supplementary research data for the paper: Marco Fontana, Davide Fantini, Giorgio Presti, Marco Tiraboschi, and Federico Avanzini. A Low-Dimensional Projection of Sound Absorption Coefficients for a Scattering Delay Network Reverberator. Journal of the Audio Engineering Society. April 2026. DOI: 10.17743/jaes.2022.0261 The repository provides additional research data for the paper. In particular, the repository includes: README.md: instructions for the data 2d_parameter_space.rar: additional data for the proposed 2D parameter space (2PS) obtained by the dimensionality reduction of an absorption coefficient dataset. reverb_matching.rar: detailed results of the reverb matching method for the estimation of absorption coefficients. These results include the comparison between the target and estimated absorption coefficients and the generated SRIRs. usability_test.rar: additional data for the usability test, including the target sets of absorption coefficients and the questionnaires submitted to the users. The paper builds upon an implementation of a Scattering Delay Network (SDN), which is available here. How to cite @article{fontana2026low, author={Fontana, Marco and Fantini, Davide and Presti, Giorgio and Tiraboschi, Marco and Avanzini, Federico}, journal={Journal of the Audio Engineering Society}, title={{A Low-Dimensional Projection of Sound Absorption Coefficients for a Scattering Delay Network Reverberator}}, doi={10.17743/jaes.2022.0261}, year={2026}, volume={74}, number={4}, pages={212-223}, month={apr}, abstract={Scattering delay networks (SDNs), a class of artificial reverberators with physically interpretable parameters, provide an efficient synthesis of room acoustics accounting for wall absorption properties. This paper builds upon a previously proposed highly parametrized and real-time implementation of an SDN, exposing octave-band absorption coefficients for each room wall. The individual manipulation of these coefficients can be challenging due to their high dimensionality. A 2D parameter space (2PS) is proposed to facilitate the navigation of the absorption coefficients. The 2PS is obtained using principal component analysis as an initial dimensionality reduction of a dataset of absorption coefficients, followed by a relaxation procedure to create a seamless 2D representation of the coefficients. A twofold evaluation of the proposed 2PS was conducted: (a) the 2PS was compared to the original space and the raw principal component analysis in a reverb matching task for the tuning of SDN coefficients, and (b) a usability test with expert audio professionals supported the potential of the 2PS from a user standpoint.} }