# Arabic Emotional Voice Conversion Using English Pre-Trained StarGANv2-VC-Based Model
## 5 Evaluation
### Automatic Recognition
#### 5.2.4. Discrete Emotion Recognition Results  
The average accuracy of 10 runs, the standard deviation, and the highest and lowest accuracy are illustrated in Table 9 for each set separately (females, males, and females with males) and for the data in the four original, converted, merged, and crossed cases. Figure 11 shows that, generally, males perform better than females in all data types, where the average male accuracy reached 77.34% compared with 71.41% for converted females. It is evident that the categorization accuracy for the crossed data is the lowest compared with other data categories. As indicated previously, the male result is likewise the highest, at 59.16%, compared with 55.59% for females and 52.75% for all data, males and females combined. Regarding the merged data, the accuracy percentage in the merged data declined by 0.94% points for females and by 3.74% points for males compared with the original data. The difference in the classification accuracy percentage between the original and the converted data sets presents more in-depth comparison. Although the classification  
Figure 11. Emotion recognition results. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Emotions**} \\ \hline  & \multicolumn{6}{c}{**Female**} & \multicolumn{6}{c}{**Male**} & \multicolumn{6}{c}{**MF**} \\ \hline  & **Ori** & **Conv** & **Mer** & **Cro** & **Ori** & **Conv** & **Mer** & **Cro** & **Ori** & **Conv** & **Mer** & **Cro** \\ \hline
**Average** & 80.38 & 71.41 & 79.44 & 55.59 & 85.48 & 77.34 & 82.41 & 59.16 & 82.52 & 66.17 & 78.78 & 52.75 \\ \hline
**Std** & 4.50 & 3.21 & 4.50 & 6.74 & 3.73 & 5.57 & 3.40 & 3.06 & 4.83 & 3.72 & 3.10 & 1.12 \\ \hline
**Highest** & 86.36 & 76.56 & 84.18 & 65.94 & 90.37 & 87.50 & 86.93 & 62.50 & 88.72 & 71.09 & 82.74 & 54.09 \\ \hline
**Lowest** & 71.21 & 67.19 & 71.43 & 45.00 & 79.26 & 68.75 & 75.83 & 52.50 & 74.06 & 57.81 & 75.13 & 50.79 \\ \hline \hline \end{tabular}
\end{table} 
Table 9. Emotion recognition average accuracy (%) results of 10 runs (Ori—original, Conv—converted, Mer—merged, Cro—crossed). accuracy score for males is generally higher, the standard deviation scale of the male group is larger than that of the female group. In addition, the gap between the highest and lowest classification accuracy for the female group is 9.37%, whereas for the male group it is 18.75%. Additionally, compared with males, the accuracy of females decreased less in the merged data compared with the original data. The confusion matrices that were obtained after running 10 iterations using the original database, converted data, merged data, and crossing data are presented in Table 10.  
Figure 12 displays each emotion independently for the four cases (for females, males, and females and males). In the case of the original, merged, and crossed data, the emotion of anger obtained the highest accuracy in the case of the females, males, and both females and males. However, in the case of the converted data, the emotion of happiness obtained the highest accuracy in the females, and the emotion of sadness got the highest accuracy in the case of the males, and both females and males. When compared with the emotions of anger and sadness, the classification accuracy for the emotions of happiness and neutrality was the lowest. The accuracy of sadness corresponds with the results of the sadness that were discussed above, where the sadness conversion results, in general, are good.