## 7 Discussion
Consequently, it could be argued that incorporating three-dimensional ensembles varying in size introduced an additional difficulty in the development of the localization model in this study, potentially degrading its localization accuracy, compared to that reported in the previous three studies presented in Table 9.  
The results of the modified image occlusion sensitivity technique showed that the frequency range between 3.5 kHz and 5 kHz is the most important in terms of the identification of the front ensembles. While caution should be exercised when comparing the \"important\" bands identified by the proposed algorithm with the results of the psychoacoustic studies in humans (machines could use their own specific way of decision making), the above frequency range is remarkably similar to one of the \"boosted bands\" associated with the localization of frontal sources as discovered by [PERSON] (3.6-5.8 kHz) [47]. According to this study, CNN used predominantly a frequency range between 1.5 kHz and 3 kHz to identify back ensembles. However, in this case, there is only a small overlap between the aforementioned band and another [PERSON]'s boosted band responsible for the localization of the back sources (0.72-1.7 kHz) [47]. As far as the localization of the up ensembles is concerned, in this work, a frequency range between 5.5 kHz and 8 kHz was identified as the most important. This outcome is similar to that obtained by [PERSON] and [PERSON] [48], who concluded that frequencies near 6-8 kHz are thought to be important for elevation \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Study**} & **Impulse Response** & **Rendering** & **Ensemble** & **Ensemble** & **Classification** & \multicolumn{2}{c}{**Test Accuracy**} \\  & **Response** & **Type** & **Locations** & **Width** & **Method** & **Room** & **Room** \\  & **Type** & & & & & **Dependent** & **Independent** \\ \hline [PERSON] and [PERSON] (2019) [20] & Reverberant & \multirow{3}{*}{2D} & 1. Front & \multirow{3}{*}{Fixed (\(\pm\)30\({}^{\circ}\))} & [PERSON] & \multirow{3}{*}{83.9\% (SVM)} & \multirow{3}{*}{56.7\% (Logit)} \\  & & & 2. Back & & & & \\  & & & 2. Back & & & & \\  & & & 3. Front \& Back & & & \\ \[PERSON] et al. (2020) [21] & Reverberant & \multirow{3}{*}{2D} & 1. Front & \multirow{3}{*}{Fixed (\(\pm\)30\({}^{\circ}\))} & [PERSON] & \multirow{3}{*}{99.4\% (CNN)} & \multirow{3}{*}{94.5\% (XGBoost)} \\  & & & 2. Back & & & & \\  & & & 2. Back & & & & \\  & & & & & & & \\ \[PERSON] et al. (2022) [22] & Anechoic (74 & \multirow{3}{*}{2D} & 1. Front & \multirow{3}{*}{Fixed (\(\pm\)30\({}^{\circ}\))} & [PERSON] & \multirow{3}{*}{99.4\% (CNN)} & \multirow{3}{*}{94.5\% (XGBoost)} \\  & & & 2. Back & & & & \\  & & & 2. Back & & & & \\  & & & & & & \\ \hline \multirow{3}{*}{This study} & Anechoic (12 & \multirow{3}{*}{3D} & 1. Front & \multirow{3}{*}{Varied (\(\pm\)15\({}^{\circ}\), \(\pm\)30\({}^{\circ}\), \(\pm\)45\({}^{\circ}\), \(\pm\)60\({}^{\circ}\), \(\pm\)75\({}^{\circ}\), \(\pm\)60\({}^{\circ}\), \(\pm\)75\({}^{\circ}\), \(\pm\)60\({}^{\circ}\), \(\pm\)75\({}^{\circ}\), \(\pm\)90\({}^{\circ}\))} & CNN & \multirow{3}{*}{89.2\% *} & \multirow{3}{*}{74.4\% *} \\  & & & 4. Down & \(\pm\)90\({}^{\circ}\)) & & & \\ \hline \hline \end{tabular}  
* For consistency with the previous studies, the accuracy values were calculated for ensemble width of \(\pm\)30\({}^{\circ}\).  
\end{table} 
Table 9: Overview of the studies regarding the automatic localization of music ensembles in binaural recordings. decoding. Moreover, they are consistent with the outcomes of the more recent study performed by [PERSON] [49], who claimed that an elevation-dependent spectral notch is located between 6 kHz and 9 kHz (note that the peaks in the importance curves in Figure 10 may refer to information encoded both as spectral peaks or notches). There are three limitations of the study that must be acknowledged. First, the impulse responses used to synthesize the binaural excerpts were anechoic.