## 6 Results
### HRTF-Independent Tests  
The previous section described the test results achieved when both the development and test sets contained the binaural excerpts synthesized using the same HRTFs. By contrast, \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ensemble Location** & **Precision [\%]** & **Recall [\%]** & **F1-Score [\%]** \\ \hline front & 57.3 (1.8) & 60.1 (1.9) & 58.6 (1.5) \\ back & 64.5 (2.5) & 61.6 (1.9) & 63.0 (1.1) \\ up & 69.1 (1.9) & 50.2 (3.0) & 58.1 (1.6) \\ down & 61.3 (1.1) & 77.6 (1.8) & 68.5 (1.1) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Classification results for the music ensembles with the width of \(\pm 90^{\circ}\). Numbers in brackets represent standard deviations. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ensemble Location** & **Precision [\%]** & **Recall [\%]** & **F1-Score [\%]** \\ \hline front & 57.3 (1.8) & 60.1 (1.9) & 58.6 (1.5) \\ back & 64.5 (2.5) & 61.6 (1.9) & 63.0 (1.1) \\ up & 69.1 (1.9) & 50.2 (3.0) & 58.1 (1.6) \\ down & 61.3 (1.1) & 77.6 (1.8) & 68.5 (1.1) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Classification results for the music ensembles with the width of \(\pm 90^{\circ}\). Numbers in brackets represent standard deviations. Figure 6: Confusion matrices obtained for different ensemble widths under the HRTF-dependent tests: (**a**) \(\pm 15^{\circ}\), (**b**) \(\pm 30^{\circ}\), (**c**) \(\pm 45^{\circ}\), (**d**) \(\pm 60^{\circ}\), (**e**) \(\pm 75^{\circ}\), (**f**) \(\pm 90^{\circ}\). this section presents the results for which the development and test sets comprised the excerpts synthesized with the \"unique\" HRTFs. The procedure taken during the HRTF-independent tests was as follows. First, all the data were split into the development and test sets, using a similar method as that applied before for the HRTF-dependent test (see Table 2) but without dividing the development set into the training and validation sets. Recall that the music recordings allocated to the development and test sets were unique (in other words, the development and test sets were different in terms of the music content). Second, the data \"within\" the development and test sets were \"filtered\" using four different data folds, as shown in Table 5. For each fold, a single HRTF corpus was removed from the development set and used solely for testing purposes. For example, for fold No. 1, the excerpts synthesized using HUTUBS corpus were removed from the development set (leaving the excerpts convolved with the remaining three corpora), whereas the excerpts obtained with the HUTUBS corpus were solely retained in the test set. Consequently, for each fold, the development and test sets were mutually exclusive in terms of the HRTF corpora (in addition to being already music content-independent). A separate CNN model was developed and tested for each data fold. The above procedure was repeated eight times. The results presented below represent the mean values across the repetitions and associated standard deviations. According to the results, for the narrowest ensembles (\(\pm 15^{\circ}\)), the average classification accuracy obtained under the HRTF-independent conditions was equal to 71.4% (SD 2.2). This result is 19.3 percentage points lower compared to that obtained earlier under the HRTF-dependent scenario. The observed difference was statistically significant at \(p<0.001\) according to \(t\)-test. This means that the outcomes of the HRTF-independent tests are more conservative compared to those achieved earlier under the HRTF-dependent tests. However, they better represent the generalization property of the developed method (capability to classify \"unknown\" samples). Figure 7 shows the classification accuracy scores obtained under the HRTF-independent test conditions as a function of the ensemble width.