# Perceptual Similarities between Artificial Reverberation Algorithms and Real Reverberation
## 2 Background
### Reverberation Algorithms for AR Scenarios  
It is impractical to apply BRIRs measured in real spaces to AR scenarios, as AR can happen in any environment, requiring a large database of impulse responses to draw from, which is not as easy as manipulating the parameters of an algorithmic reverb [16]. Furthermore, measuring an impulse response is non-trivial, and multiple measurements are required for real-time interpolation if adaptive dynamic reverberation processing based on any user position is the goal [12; 17]. There have been many significant efforts as of the time of writing in the application of computational reverberation algorithms for convincing AR. [PERSON] et al. proposed a technique and application of Wearable AR Audio (WARA) [18]. The model's direct sound and 14 early reflections (six first-order and eight lateral planar second-order early reflections) were calculated from a simple shoebox room model with user-adjustable wall, floor, and ceiling positions. To match the length of the reverberation to that of the pseudo-acoustic environment, diffuse late reverberations were added using a variant of a Feedback Delay Network (FDN). The parameters of the reverberation algorithm (e.g. reverberation time) were set manually by analysing the reverberation of the environment or estimating parameters automatically from the binaural microphone signals. The additional information about the user's orientation and position required for room modelling and binaural synthesis was estimated using a number of head-tracking devices. A real-time binaural room modeling proposal for AR applications based on Scattering Delay Network (SDN) reverberation was presented by [PERSON], et al. in 2021 [19]. The combination of Digital Waveguide Network (DWN) and ray-tracing Image Source Method (ISM) approaches for SDN reverberation provides physical accuracy close to room simulation models while meeting the lower processing requirements of other reverberators that use delay networks [19; 20; 21]. A study by [PERSON] et al. [22] indicated that SDNs are considered more natural than binaural room impulse responses, ray tracing, and feedback delay networks in evaluations based on non-interactive simulations of two listening rooms. However, the suitability of SDNs for AR applications needs to be determined, as binaural SDN models have not been proposed in real-time architectures suitable for mobile or wearable computing devices [19]. Because this paper evaluates artificial reverberation algorithms based on delayed networks, SDN reverberation based on digital waveguide networks (DWN) and ray-traced image source models are not included among the studied algorithms. Moreover, the main disadvantage of computational acoustics is that the transfer operators take up a large memory footprint when sound propagates between surfaces, with the result that computational methods encounter a bottleneck [23; 24]. Conversely, artificial reverberation algorithms based on delay network structures have flexible parameterization characteristics and better real-time performance [25]. It is useful to examine the output of such algorithms by looking at their response to a discrete unit sample function [26] passing through various filters and delay lines and feedback connections. This is equivalent to visualization of RIRs, and is readily achieved within the MATLAB environment [27], which has a rich filter structure database. In addition to recursive filters based on delay networks, simple finite impulse response (FIR) filters can be used to implement early reflection simulations. As a filter with no feedback support, FIR filters can be designed with arbitrary amplitude-frequency characteristics while maintaining strict linear phase characteristics, and are widely used in speech and data transmission [28]. However, because the filter has no feedback, more coefficients are required in the system equations [29]. For the purposes of AR, simplicity, real-time performance and computational efficiency must be considered.