Research Article
A High-Efficiency Fatigued Speech Feature Selection Method for Air Traffic Controllers Based on Improved Compressed Sensing
Table 2
The fatigue dataset utilized in this study.
| Fatigue data set | Number | Expression | Explanation |
| | 1 | Control category | R, area control; A, approach control; T, tower control | | 2 | ATC rank | 5, level 5; 4, level 4; 3, level 3; 2, level 2; 1, level 1; 0, trainee | | 3–10 | Time (UTC) | 3–6, time of starting work; 7–10, time of ending work | | 11 | Sex | F, female; M, male | | 12 and 13 | Age | Arabic numeral (age in years) | | 14 and 15 | Order | Nn, N is a digital indicator and n is an Arabic numeral indicating the nth instruction issued by the ATC while working | | 16 and 17 | Status | 14th, “-;” 15th, voice command; 1, error; 2, ambiguity; 3, hesitation or pause; 4, fatigue |
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