Table 3.
Test Set Accuracies for all 12 Methods Developed
| DESCRIPTION | HIGHEST TEST SET ACCURACY |
|---|---|
| MFCC, L1, RBF-SVM | 0.99 |
| MFCC, L2, RBF-SVM | 0.96 |
| MFCC, RBF-SVM | 0.93 |
| MFCC, tree-based, RBF-SVM | 0.86 |
| Autoencoder, linear-SVM | 0.81 |
| MFCC, linear-SVM | 0.74 |
| Autoencoder, RBF-SVM | 0.73 |
| Grayscale images, RBF-SVM | 0.73 |
| nFrames, L1, RBF-SVM | 0.55 |
| Grayscale images, linear-SVM | 0.52 |
| Grayscale images, logistic regression | 0.46 |
| Convolutional neural network | 0.46 |
MFCC, mel-frequency cepstral coefficient; RBF, radial basis function; SVM, support vector machine.