## Appendix B Confusion Matrices for BUZZ1 and BUZZ2 Validation Datasets  
This appendix gives confusion matrices for the DL and ML models on the BUZZ1 and BUZZ2 validation datasets.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 297 & 3 & 0 & 300 & 99.00\% \\ Noise & 250 & 100 & 0 & 350 & 28.57\% \\ Cricket & 29 & 17 & 454 & 500 & 90.80\% \\ Total Accuracy & & & & & 74.00\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Confusion matrix for ConvNet 1 with receptive field size \(n\) = 80 on BUZZ1 validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 300 & 0 & 0 & 300 & 100\% \\ Noise & 4 & 346 & 0 & 350 & 98.85\% \\ Cricket & 0 & 101 & 399 & 500 & 79.80\% \\ Total Accuracy & & & & & 90.86\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Confusion matrix for RawConvNet with receptive field size \(n\) = 10 on BUZZ1 validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 300 & 0 & 0 & 300 & 100\% \\ Noise & 54 & 77 & 369 & 500 & 73.80\% \\ Total Accuracy & & & & & 83.91\% \\ \hline \hline \end{tabular}
\end{table}
Table 12: Confusion matrix for ConvNet 1 with receptive field \(n=80\) on BUZZ2 on validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 300 & 0 & 0 & 300 & 100\% \\ Noise & 16 & 334 & 0 & 350 & 95.42\% \\ Cricket & 0 & 62 & 438 & 500 & 87.60\% \\ Total Accuracy & & & & & 93.21\% \\ \hline \hline \end{tabular}
\end{table}
Table 10: Confusion matrix for KNN with \(n=5\) and no feature scaling on BUZZ1 validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 300 & 0 & 0 & 300 & 100\% \\ Noise & 54 & 77 & 369 & 500 & 73.80\% \\ Total Accuracy & & & & & 83.91\% \\ \hline \hline \end{tabular}
\end{table}
Table 11: Confusion matrix for SVM OVR with no feature scaling on BUZZ1 validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 865 & 134 & 1 & 1000 & 86.5\% \\ Noise & 244 & 667 & 89 & 1000 & 66.7\% \\ Cricket & 0 & 43 & 957 & 1000 & 95.7\% \\ Total Accuracy & & & & & 82.96\% \\ \hline \hline \end{tabular}
\end{table}
Table 13: Confusion matrix for ConvNet 2 with receptive field \(n=80\) on BUZZ2 validation dataset.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{_True_} & \multicolumn{6}{c}{_Predicted_} \\ \cline{2-7}  & **Bee** & **Noise** & **Cricket** & **Total** & **Validation Accuracy** \\ \hline Bee & 766 & 178 & 56 & 1000 & 76.6\% \\ Noise & 152 & 776 & 72 & 1000 & 77.6\% \\ Cricket & 0 & 36 & 964 & 1000 & 96.4\% \\ Total Accuracy & & & & & 83.53\% \\ \hline \hline \end{tabular}
\end{table}
Table 13: Confusion matrix for ConvNet 2 with receptive field \(n=80\) on BUZZ2 validation dataset.