## 3 Results and Discussion
### Results of the Analysis of the Hybrid Features with GRU-Based Training  
According to the results presented in the tables, the best accuracy was obtained using EZDDMFCC for all window types, window sizes, classification methods, and speaker gender. This might be due to  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Windows**} & \multicolumn{5}{c}{**Classification Type and Performance (\%)**} \\ \hline
**Type** & **Size (ms)** & **CNN** & **MLP** & **Naive Bayes** & **SVM** & **Random Forest** & **k-NN** \\ \hline \multirow{4}{*}{Hamming} & 20 & 91.61 & 83.86 & 71.01 & 81.57 & 85.08 & 84.35 \\  & 25 & 91.11 & 82.34 & 72.11 & 81.43 & 84.97 & 83.22 \\  & 30 & 91.20 & 83.18 & 72.76 & 80.91 & 84.13 & 84.43 \\  & 35 & 91.14 & 82.12 & 72.93 & 80.79 & 84.11 & 83.07 \\ \hline \multirow{4}{*}{Hanning} & 20 & 91.00 & 82.10 & 71.58 & 80.1306 & 84.76 & 84.32 \\  & 25 & 91.34 & 82.70 & 71.19 & 80.7541 & 86.30 & 85.14 \\  & 30 & 91.66 & 82.03 & 72.77 & 81.2109 & 85.14 & 84.22 \\  & 35 & 91.31 & 82.10 & 71.91 & 80.9700 & 86.02 & 83.36 \\ \hline \multirow{4}{*}{Rectangular} & 20 & 91.22 & 82.16 & 71.02 & 80.8215 & 86.12 & 85.54 \\  & 25 & 91.01 & 82.30 & 71.46 & 80.6337 & 85.00 & 85.47 \\ \cline{1-1}  & 30 & 91.41 & 82.57 & 72.18 & 81.0198 & 84.22 & 84.72 \\ \cline{1-1}  & 35 & 91.60 & 83.70 & 72.29 & 80.9412 & 84.16 & 83.71 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Performance accuracy for female speakers based on GRU+EZMFCC.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Windows**} & \multicolumn{5}{c}{**Classification Type and Performance (\%)**} \\ \hline
**Type** & **Size (ms)** & **CNN** & **MLP** & **Naive Bayes** & **SVM** & **Random Forest** & **k-NN** \\ \hline \multirow{4}{*}{Hamming} & 20 & 93.14 & 85.79 & 73.28 & 84.54 & 88.29 & 87.40 \\  & 25 & 93.37 & 87.31 & 73.44 & 85.63 & 88.41 & 85.64 \\  & 30 & 92.15 & 86.76 & 74.12 & 84.52 & 88.70 & 86.81 \\  & 35 & 93.50 & 87.61 & 74.59 & 84.25 & 89.57 & 86.26 \\ \hline \multirow{4}{*}{Hanning} & 20 & 93.01 & 85.28 & 74.25 & 84.31 & 90.45 & 87.52 \\  & 25 & 93.30 & 86.39 & 74.02 & 84.29 & 88.07 & 86.89 \\  & 30 & 93.08 & 87.20 & 73.20 & 84.51 & 88.42 & 86.18 \\  & 35 & 92.51 & 87.28 & 73.57 & 84.44 & 89.90 & 86.87 \\ \hline \multirow{4}{*}{Rectangular} & 20 & 92.26 & 87.11 & 74.18 & 84.25 & 88.57 & 87.83 \\  & 25 & 93.18 & 86.04 & 74.15 & 84.34 & 90.20 & 87.63 \\  & 30 & 93.88 & 86.57 & 74.82 & 84.56 & 89.27 & 87.60 \\  & 35 & 93.52 & 86.13 & 74.64 & 85.32 & 88.82 & 86.47 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Performance accuracy for female speakers based on GRU+EZDMFCC.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Windows**} & \multicolumn{5}{c}{**Classification Type and Performance (\%)**} \\ \hline
**Type** & **Size (ms)** & **CNN** & **MLP** & **Naive Bayes** & **SVM** & **Random Forest** & **k-NN** \\ \hline \multirow{4}{*}{Hamming} & 20 & 95.10 & 91.30 & 75.51 & 86.29 & 92.20 & 91.16 \\  & 25 & 95.09 & 90.61 & 78.84 & 86.17 & 92.36 & 91.27 \\  & 30 & 95.03 & 90.87 & 77.21 & 86.94 & 91.44 & 91.35 \\  & 35 & 94.67 & 90.12 & 77.54 & 86.75 & 91.78 & 91.41 \\ \hline \multirow{4}{*}{Hanning} & 20 & 94.82 & 89.48 & 78.31 & 86.01 & 92.12 & 91.64 \\  & 25 & 94.31 & 91.85 & 76.33 & 87.20 & 91.05 & 92.30 \\  & 30 & 94.93 & 91.70 & 77.82 & 86.76 & 92.80 & 91.54 \\  & 35 & 95.63 & 90.62 & 77.77 & 86.10 & 92.44 & 91.30 \\ \hline \multirow{4}{*}{Rectangular} & 20 & 95.30 & 91.47 & 78.60 & 87.27 & 92.30 & 91.30 \\  & 25 & 94.16 & 90.56 & 79.80 & 87.05 & 92.49 & 92.20 \\ \cline{1-1}  & 30 & 94.14 & 91.57 & 78.01 & 87.37 & 91.33 & 91.73 \\ \cline{1-1}  & 35 & 95.05 & 91.13 & 77.12 & 87.53 & 92.70 & 92.17 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Performance accuracy for female speakers based on GRU+EZDDMFCC.  
the number of novel features existing in EZDDMFCC as a result of double derivation of the MFCC. The feature dimension of EZDDMFCC was higher than the others. However, it took longer time to compute, as seen in Table 10.