## 4 Evaluation Procedure
### Benchmark Results  
In general, the testing of the model's performance was conducted using the same _BL_ model, which was used for the _BL_ matrix construction. The _BL_ analysis exports the benchmark of all inputs and outputs of the real and virtual components. The results show the model's prediction of the binaural loudness and the adaptive mix's response. Figure 11: ARA headphones and preamp. Figure 12: Adaptive ARA mix GUI. Figure 13, shows the spectrum analysis of the pure tone of 1 kHz at different dB SPL levels. The tone of 65 dB SPL (see Figure 13a), represents the virtual input of the system, and the tone of 85 dB SPL (see Figure 13b), the real component. Figure 13c presents the virtual output of the \(BL\) adaptation according to the real component. The form of the spectrum does not have any difference except for an increase in its energy. In terms of spectrum analysis, data from Table 2 show the increase of \(BL\) in the virtual output according to a real input tone of 1 kHz at 85 dB. The model seems to work well in this simple occasion of the ARA scenario. Figure 14 shows the case of an ARA scenario of an artificial sound integrated in the real environment of a car traffic soundscape. According to the results in Figure 14c, the \(BL\) ARA mix model seems to preserve the originality of the virtual component (Figure 14a). After the adaptive ARA mix model, the form of the Test-1 virtual input and output seems to have characteristics with energy modifications, which are relative to the changes in coloration of the \(BL\) virtual output according to the real environment. Besides the frequency spectrum analysis, the loudness of each sample was measured for its loudness with the \(BL\) model [38]. Table 3 provides the results of the \(BL\) analysis of the virtual input and the real environment, and the result of the \(BL\) ARA mix model. The results show a decrease in loudness of the virtual output compared to the virtual input, whereas the final loudness is close to the real input of the traffic. This modification has not destroyed the final form of the spectrum, and so the virtual output does not include audible distortions. \begin{table}
\begin{tabular}{c c} \hline \hline
**ARA Components** & \(BL\) (Phons) \\ \hline Virtual Input Tone 1 kHz 65 dB & 68.36 \\ Real Input Tone 1 kHz 85 dB & 82.43 \\ \(BL\) Virtual Output 1 kHz 65 dB & 82.80 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: \(BL\) inputs and output of 1 kHz tones. Figure 13: Spectrum analysis of \(BL\) mix input-output. (a) Tone 1000 Hz 65 dB (virtual source). (b) Tone 1000 Hz 85 dB (real environment). (c) \(BL\) tone 1000 Hz 65 dB (\(BL\) mix result). The last ARA mix pair examined was the Test-1 virtual sound according to the previous test mixed with the real environment consisting of forest sounds. The results of the spectrum analysis are shown in Figure 15. The real environment of the forest appears to have increased energy in a broad frequency spectrum. The model seems to have changed the spectrum of the virtual component according to the energy of missing frequencies. This analysis does not show the loudness of the audio result in comparison to the real and virtual environment. Table 4, shows the estimation of the \(BL\) of ARA mix components. According to this, it seems that the model has adapted the virtual component (77.17 Phons) to the real environment input (72.46 Phons), resulting in the final adapted virtual output at 72.85 Phons. The adapted virtual environment has \(BL\) very close to the real environment, thus integrating acoustically the latter's coloration characteristics while maintaining the originality of the virtual sources. Overall, the results derived from the spectrum analysis of the ARA mix components and the calculation of each one's \(BL\) indicate that the \(BL\) ARA mix model integrates the virtual environment in the real environment in a smooth way. Nevertheless, more research needs to be done to address a wide variety of different types of sound in order for the \(BL\) ARA mix model to be improved and optimized.