Table 1. Classification results (%)
Feature set | Accuracy | ASD | TD |
Precision | Recall | F1-score | Precision | Recall | F1-score |
eGeMAPS | All (88) | 88.08 | 88.12 | 99.90 | 93.64 | 78.57 | 2.66 | 5.14 |
RFE (70) | 88.29 | 88.62 | 99.43 | 93.72 | 65.31 | 7.73 | 13.82 |
KDSFs | All (29) | 91.25 | 92.23 | 98.33 | 95.18 | 76.85 | 40.10 | 52.70 |
RFE (19) | 90.78 | 94.55 | 94.99 | 94.77 | 62.50 | 60.39 | 61.43 |
Subset of KDSFs | Pitch+MFCC (18) | 91.08 | 93.05 | 97.09 | 95.03 | 69.37 | 47.58 | 56.45 |
VQ+MFCC (18) | 91.90 | 95.45 | 95.32 | 95.39 | 66.51 | 67.15 | 66.83 |
SR+MFCC (21) | 92.13 | 95.40 | 95.66 | 95.53 | 67.98 | 66.67 | 67.32 |
The best performances are in bold. The number in parenthesis denotes the number of features used for training the classifiers.
ASD, autism spectrum disorder; TD, typical development; eGeMAPS, extended Geneva Minimalistic Acoustic Standard Parameter Set; RFE, recursive feature elimination; KDSFs, knowledge-driven speech features; VQ, voice quality; MFCC, Mel-frequency cepstral coefficient; SR, speech rate.