Baykaner, K;
Huckvale, M;
Whiteley, I;
Ryumin, O;
Andreeva, S;
(2015)
The prediction of fatigue using speech as a biosignal.
In: Dediu, Adrian-Horia and Martín-Vide, Carlos and Vicsi, Klára, (eds.)
Proceedings of International Conference on Statistical Language and Speech Processing - SLSP 2015.
(pp. pp. 8-17).
Springer: Budapest, Hungary.
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Abstract
Automatic systems for estimating operator fatigue have application in safety-critical environments. We develop and evaluate a system to detect fatigue from speech recordings collected from speakers kept awake over a 60-hour period. A binary classification system (fatigued/not-fatigued) based on time spent awake showed good discrimination, with 80 % unweighted accuracy using raw features, and 90 % with speaker-normalized features. We describe the data collection, feature analysis, machine learning and cross-validation used in the study. Results are promising for real-world applications in domains such as aerospace, transportation and mining where operators are in regular verbal communication as part of their normal working activities.
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