Vocal Fatigue in Mandarin-Speaking Teachers: Characteristics of Phonation and Resonance

Objective: To investigate phonatory and resonatory characteristics in Mandarin-speaking female teachers with vocal fatigue (VF). Methods: A case-control study was conducted among teachers in Shanghai, China. Participants included 18 vocal-fatigued teachers (VF), 17 non-vocal-fatigued teachers (NVF), and 16 nonoccupational voice users (NOVU). Subjective assessment included the Vocal Fatigue Index (VFI), Voice Handicap Index-10 (VHI-10), and GRBAS scale. Objective assessments included maximum phonation time (MPT), dysphonia severity index (DSI), fundamental frequency (F0), cepstral peak prominence, intensity, jitter, shimmer, harmonics-to-noise ratio (HNR), the rate, and regularity (jitter) of the laryngeal diadochokinesis (LDDK) (/ʔa/, /ha/, /ʔʌ/, /hʌ/). Articulatory features included vowel space area (VSA), formant centralization ratio (FCR), the formants (F1-F3), and their bandwidths (B1-B3). These measures were collected during vowels, passage reading, and free talking. A decision tree model was developed to identify key factors associated with VF. Results: Subjective voice assessments: the VF group showed significantly higher VHI-10 scores and grade (G) ratings of GRBAS compared with the NVF and NOVU (P < 0.05). Objective voice assessments: the VF had significantly lower DSI (P < 0.05), higher FCR, F1/i/, and F1/u/ (P < 0.05) than NVF and NOVU, and reduced MPT and VSA compared with the NVF (P < 0.05). F2/u/ was significantly higher in the VF than in the NVF (P < 0.05). Compared with the NOVU, the VF exhibited significantly higher jitter/i/, F2/a/, and B3/u/ (P < 0.05), as well as significantly lower HNR/u/, F2/i/, B3/i/, /ha/, and /hʌ/ rate (P < 0.05). Decision tree model: F2/u/, VHI-10, and DSI were identified as key discriminators of VF in teachers. Conclusions: Teachers with VF demonstrate insufficient respiratory support, poor vocal quality, reduced LDDK ability, and limited articulatory movement range. F2/u/, VHI-10, and DSI play a crucial role in distinguishing VF.