Voice fatigue subtyping through individual modeling of vocal demand reponses - Berardi, Mark L.; Whitling, Susanna; Hunter, Eric J. (Scientific Reports, 2025)
Recognizing individual variability is essential for developing targeted, personalized medical interventions. Vocal fatigue is a prevalent symptom and complaint among occupational voice users, but its identification has yielded mixed results. Vocal fatigue is a complex issue with heterogeneous biophysiological responses to vocal demands among individuals. This research aims to classify individuals as vocal demand responders to measure changes in vocal performance consistent with state vocal fatigue. A total of 37 participants (19F, 18M) completed a 30-minute vocal loading task (VLT) which consisted of loud speaking with background noise. Participants provided speech samples pre- and post-VLT and rated their vocal effort levels before, every 5 minutes during, and after the VLT. Perceived effort ratings and measured vocal performance from the speech samples were used to classify participants into distinct subgroups of vocal demand responders. Prior to classification there were few detectable changes associated with the VLT. However, the subgroup with both vocal effort and voice production demand responses displayed significant changes consistent with vocal fatigue while the other subgroups did not. These findings support the need for an individual-based approach to subtyping and measuring vocal fatigue and highlight its heterogeneous nature.
Keywords: Machine learning; Precision medicine; Vocal fatigue; Vocal loading task; Voice production