# Perceptual Similarities between Artificial Reverberation Algorithms and Real Reverberation
## 6 Conclusions  
This experiment evaluated the similarity between different artificial reverberation algorithms and measured reverberation, including the assessment of a novel reverberation algorithm, the HMS. The motivation for the study was to consider the suitability of reverberation algorithms to be applied to AR scenarios in the future to create more plausible reverberation effects. In the long reverberation time, the simulation of the Gardner reverberation algorithm was perceived as closer to the measured perceptual reverberation, while the simulation of HMS and Schroeder reverberation algorithms were more similar in the short and medium reverberation times. In addition, across all twelve stimuli, the HMS reverberation algorithm obtained the seven highest scores in the twelve stimuli tested. Except for the female singing in the long reverberation, there was no significant difference between the HMS reverberation algorithm and the reverberation algorithm with the highest score in the other eleven stimuli. The Schroeder reverberation algorithm is a good choice if perceptual performance is not particularly important and computational efficiency is required. Alternatively, based on the absolute advantage of the Gardner reverberation algorithm in simulating real reverberation under long reverberation times, a combination of HMS and Gardner or Schroeder and Gardner algorithms could be a way forward for AR scenes. Future work should investigate the combination of the Gardner and HMS reverberation algorithms into a set of algorithms that simulate room models with different reverberation times using head tracking and an AR framework to realise dynamic reverberation. Conceptualisation, H.M. and G.K.; methodology, H.M., G.K. and H.D. ; software, H.M.; validation, H.M.; formal analysis, H.M.; investigation, H.M.; resources, H.M., G.K. and H.D. ; data curation, H.M.; writing--original draft preparation, H.M.; writing--review and editing, G.K. and H.D. ; visualization, H.M.; supervision, G.K. and H.D. ; project administration, H.M. funding acquisition, G.K. All authors have read and agreed to the published version of the manuscript. This research was supported by the Engineering and Physical Sciences Research Council IAA project \"MINERVA: Musical Interactions in Networked Experiences using Real-time Virtual Audio\". The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of University of York (protocol code Mi070821 and 9 August 2021 of approval). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper. The data presented in this study are available in insert article. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: \begin{tabular}{l l} AR & Augmented Reality \\ BRIR & Binaural room impulse response \\ DFDN & Directional Feedback Delay Network \\ D/R & Direct-to-reverberant \\ ERB & Equivalent Rectangular Bandwidth \\ DWN & Digital Waveguide Networks \\ FDN & Feedback Delay Network \\ FDTD & Finite-difference Time-Domain \\ FIR & Finite impulse response \\ FTP & File Transfer Protocol \\ HMS & Hybrid Moorer-Schroeder \\ HRTFs & head related transfer functions \\ IACC & Interaurual Cross-correlation Coefficient \\ ISM & Image Source Mode \\ LPF & Low pass feedback \\ MUSHRA & Multiple Stimuli with Hidden Reference and Anchor \\ RIR & Room impulse response \\ SDN & Scattering Delay Network \\ WARA & Wearable Augmented Reality Audio \\ \end{tabular}   
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