# Auralization of High-Order Directional Sources from First-Order RIR Measurements
## 3 Listening Experiment--Comparative Study
### Auralization Techniques--Virtualizations of the IKO  
As acoustic virtualizations of the IKO, we compared five different auralization techniques in the listening experiment. The block diagram in Figure 3 depicts these techniques and their details are given below. The ear signals \(y_{l}(t)\) and \(y_{r}(t)\) are obtained by running the source signal through several processing stages. Those stages include (i) beam encoding, (ii) IKO control, (iii) directivity, (iv) room transfer function, (v) Ambisonics encoding, and finally (vi) the dynamic binaural rendering. With the source signal \(x(t)\) and the desired beam direction \(\varphi_{S}\), the frequency independent encoder outputs the order \(N_{B}\) Ambisonics representation of the beam. The processing in the _Beam Encoding_ stage is independent of the auralization technique. In the _IKO Control_ stage the \((N_{B}+1)^{2}\) channels are mapped to 20 loudspeaker signals of the IKO using the frequency-dependent _IKO Filters_. A measurement based approach for designing the multiple-input multiple-output (MIMO) IKO control filters is presented in [40]. It is based on laser Doppler vibrometry measurements and allows for control of side-lobe suppression and excursion-limiting filter design. The designed beam patterns were verified by far-field extrapolated measurements from a surrounding microphone array. The IKO's beamforming can be analyzed by using the open source tool balloon_holo, which is part of IEM's Open Data Project ([[https://opendata.iem.at/projects/dirpat/](https://opendata.iem.at/projects/dirpat/)]([https://opendata.iem.at/projects/dirpat/](https://opendata.iem.at/projects/dirpat/))). All underlying measurements (laser Doppler vibrometry and pressure of a surrounding microphone array) as well as the corresponding _IKO Filters_ can be found  
Figure 3: Auralization techniques evaluated in the listening experiment. Here \(x(t)\), \(\varphi_{S}\), and \(y_{l}(t)\) and \(y_{r}(t)\) are the source signal, the beam direction, and the ear signals of the left and right ear, respectively. The auralization techniques from top to bottom are (i) dummy head BRIR (\(Dy\)), (ii) MIMO ARIR (\(Em\)), (iii) Multi ASDM (\(As\)), (iv) real SRD ARIR (\(Sr\)), and (v) ideal SRD ARIR (\(Si\)) auralization. Note that gray-shaded boxes indicate functional blocks which are shared between different techniques. The boxes delimited by bold lines mark techniques in which the actual _Room Transfer Function_ is not directly measured but obtained by processing (e.g., upscaling by an ASDM method) of the underlying measurements as proposed in Section 2.2. A detailed description of the techniques can be found throughout Section 3.1.  
online ([[https://phaidra.kug.ac.at/o:67609](https://phaidra.kug.ac.at/o:67609)]([https://phaidra.kug.ac.at/o:67609](https://phaidra.kug.ac.at/o:67609))) and a summary is presented in [13]; here, we used the IEM IKO3 ([[https://phaidra.kug.ac.at/o:75316](https://phaidra.kug.ac.at/o:75316)]([https://phaidra.kug.ac.at/o:75316](https://phaidra.kug.ac.at/o:75316))). In the latest stage, _Dynamic Binural Rendering_ of the Ambisonic scene is obtained by a convolution of the rotated Ambisonic signals with any state-of-the-art FIR binaural Ambisonic renderer. Here, we employ the time-invariant filters of the MagLS (magnitude-least-squares) renderer (The MagLS renderer is part of the IEM plugin suite which can be found here [[https://plugins.iem.at/](https://plugins.iem.at/)]([https://plugins.iem.at/](https://plugins.iem.at/))) defined in [18,41] to get high-quality Ambisonic rendering already with an order as low as \(N=3\). The perceptual quality improvement of these filters is achieved by using a magnitude-least-squares optimization that disregards phase match in favor of an improved HRTF magnitude at high frequencies. MagLS as outlined in [18,36] also includes an interaural covariance correction that offers an optimal compromise for consistently rendering diffuse fields.