Suitability of Game Engines for Virtual Acoustic Experiments

Kamaris G, Giannatsis E, Kaleris K, Mourjopoulos J. Suitability of Game Engines for Virtual Acoustic Experiments. In: AES Convention 146. Audio Engineering Society; 2019. Paper 524. Available from: https://aes.org/publications/elibrary-page/?id=20382

@inproceedings{Kamaris2019_20382,
  author = {Kamaris, Gavriil and Giannatsis, Eftratios and Kaleris, Konstantinos and Mourjopoulos, John},
  title = {{Suitability of Game Engines for Virtual Acoustic Experiments}},
  booktitle = {AES Convention 146},
  note = {Paper 524},
  year = {2019},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=20382}
}

TY  - CPAPER
TI  - Suitability of Game Engines for Virtual Acoustic Experiments
AU  - Kamaris, Gavriil
AU  - Giannatsis, Eftratios
AU  - Kaleris, Konstantinos
AU  - Mourjopoulos, John
T2  - AES Convention 146
M1  - Paper 524
PY  - 2019
DA  - 2019/03/06
UR  - https://aes.org/publications/elibrary-page/?id=20382
PB  - Audio Engineering Society
LA  - en
AB  - Game engines like Unity [1], are recently becoming widely used not only by the game industry but also in the creation of serious games and for animations by the movie industry. The enhanced audio spacialisation assets that have been developed for such platforms [2], may also provide a suitable development environment for interactive acoustic auralisation and hence may allow the evolution of controlled acoustic and perceptual experiments within such “virtual laboratory” spaces. Here, the above concept is investigated via some preliminary experiments assessing virtual source localisation achieved by using such a virtual platform within a stereo loudspeaker virtual set-up, when compared to the localisation achieved using an established auralisation method and a listener test. In all cases, the source localisation is compared to the ideal (intended - ground truth) image source positions and the estimated differences are quantified via a perceptual binaural model [3].
ER  -