Abstract:
In this new research, we expand on our previous system for vocal fatigue detection by adding five new features in the classifier. We also perform further testing on 37 te...Show MoreMetadata
Abstract:
In this new research, we expand on our previous system for vocal fatigue detection by adding five new features in the classifier. We also perform further testing on 37 test subjects. The goals were: 1) to classify subjects performing normal versus simulated pressed vocal gestures; 2) to distinguish vocally healthy from vocally fatigued subjects as determined by VFI score on factor 1; and 3) to determine the validity of the labels vis-a-vis the choice of this same VFI-factor-1 boundary. As the results demonstrated, the choice of classifier and the new features were quite appropriate, while there is margin for better choices of the VFI-factor-1 boundary.
Published in: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date of Conference: 18-21 July 2018
Date Added to IEEE Xplore: 28 October 2018
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PubMed ID: 30441467