Research Article
Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features
Table 1
Summary of speech features.
| Main category | Subcategory | Number of features | Functions |
| MFCC | MFCC (0–14) | 630 | Corresponding delta coefficients appended | SPEC | Flux | 42 | 21 functions utilized | | Centroid | 42 | maxPos, minPos | | Entropy | 42 | Mean, std dev | | Roll-off | 168 | Skewness, kurtosis | | Band energies | 84 | Quartile 1/2/3 | PROS | PCM loudness | 42 | Quartile range (2–1)/(3–2)/(3–1) | | Log mel-frequency band (0–7) | 336 | Linear regression error Q/A | | LSP frequency (0–7) | 336 | Linear regression coeff. 1/2 | | F0 envelope | 42 | Percentile 1/99 | | Voicing probability | 42 | Percentile range (99–1) | | F0final, ShimmerLocal | 76 | 19 functions by eliminating the minimum value and the | | JitterLocal, JitterDDP | 76 | Range functions from the 21 abovementioned functions | | Pitch onsets, duration | 2 | No functions | GLOT | GLT | 27 | Mean, max, min | | GLF | 5 | Mean, max, min | Total | | 1992 | |
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