Table 4 Accuracy performance of emotion recognition [%] without selection (–) in comparison with two different selection methods (FMS and SFS) and extraction (S-PCA) methods using k-NN algorithm as a classifier
From: Efficiency of chosen speech descriptors in relation to emotion recognition
Acted speech | Natural speech | |||||||
|---|---|---|---|---|---|---|---|---|
– | SFS | FMS | S-PCA | – | SFS | FMS | S-PCA | |
f 0 | 31.6 | 38.4 | 40.92 | 32.9 | 39.8 | 40.9 | 46.58 | 40.9 |
f 1−f 3 | 38.8 | 39.2 | 38.8 | 34.2 | 39.5 | 39.6 | 45.73 | 37.1 |
Energy | 30.4 | 36.7 | 36.7 | 31.6 | 47 | 47.7 | 55.96 | 44.6 |
LPC | 36.7 | 36.7 | 36.7 | 36.3 | 57.8 | 57.8 | 63.06 | 48.5 |
BFCC | 55.7 | 64.4 | 64.4 | 51.5 | 76.7 | 77.7 | 76.7 | 71.1 |
MFCC | 56.5 | 59.9 | 58.10 | 40.5 | 71.7 | 74 | 74 | 62.7 |
HFCC | 51.1 | 52.7 | 52.7 | 45.6 | 70.4 | 72.9 | 75.61 | 68.8 |
PLP | 54 | 54.4 | 57.25 | 51.9 | 71.4 | 71.4 | 71.4 | 70.4 |
RPLP | 55.7 | 58.6 | 59.9 | 51.9 | 70 | 71.3 | 71.38 | 64.2 |
RASTA | 43 | 46.8 | 49.36 | 35 | 52.2 | 52.2 | 72.76 | 44.1 |