Supplementary materials to the paper: Riccardo Bona, Davide Fantini, Giorgio Presti, Marco Tiraboschi, Isaac Engel and Federico Avanzini. 2022. Automatic Parameters Tuning of Late Reverberation Algorithms for Audio Augmented Reality. In Proceedings of International Conference on Audio Mostly. The supplementary materials include the reverberated audio stimuli employed in the MUSHRA listening test reported in the paper. For each type of audio stimuli (Drums, Sax and Speech) the version reverberated with each of the six target Room Impulse Responses (RIRs) is provided along with the versions reverberated using the reverb matching method proposed in the paper (two different artificial reverberators have been considered: FDN and Freeverb). Further, the reverberation times (\(T_{20}\)) per octave band for each considered RIR are provided.

{"references": ["Riccardo Bona, Davide Fantini, Giorgio Presti, Marco Tiraboschi, Isaac Engel and Federico Avanzini. 2022. Automatic Parameters Tuning of Late Reverberation Algorithms for Audio Augmented Reality. In Proceedings of International Conference on Audio Mostly."]}

This work is part of SONICOM, a project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101017743.