ABSTRACT
COVID-19 pandemic has posed serious risk of contagion to humans. There is a need to find reliable non-contact tests like vocal correlates of COVID-19 infection. Thirty-six Asian ethnic volunteers 16 (8M & 8F) infected subjects and 20 (10M &10F) non-infected controls participated in this study by vocalizing vowels /a/, /e/, /i/, /o/, /u/. Voice correlates of 16 COVID-19 positive patients were compared during infection and after recovery with 20 non-infected controls. Compared to non-infected controls, significantly higher values of energy intensity for /o/ (p = 0.048); formant F1 for /o/ (p = 0.014); and formant F3 for /u/ (p = 0.032) were observed in male patients, while higher values of Jitter (local, abs) for /o/ (p = 0.021) and Jitter (ppq5) for /a/ (p = 0.014) were observed in female patients. However, formant F2 for /u/ (p = 0.018), mean pitch F0 for /e/, /i/ and /o/ (p = 0.033; 0.036; 0.047) decreased for female patients under infection. Compared to recovered conditions, HNR for /e/ (p = 0.014) was higher in male patients under infection, while Jitter (rap) for /a/ (p = 0.041); Jitter (ppq5) for /a/ (p = 0.032); Shimmer (local, dB) for /i/ (p = 0.024); Shimmer (apq5) for /u/ (p = 0.019); and formant F4 for vowel /o/ (p = 0.022) were higher in female patients under infection. However, HNR for /e/ (p = 0.041); and formant F1 for /o/ (p = 0.002) were lower in female patients compared to their recovered conditions. Obtained results support the hypothesis since changes in voice parameters were observed in the infected patients which can be correlated to a combination of acoustic measures like fundamental frequency, formant characteristics, HNR, and voice perturbations like jitter and shimmer for different vowels. Thus, voice analysis can be used for scanning and prognosis of COVID-19 infection. Based on the findings of this study, a mobile application can be developed to analyze human voice in real-time to detect COVID-19 symptoms for remedial measures and necessary action.
ABSTRACT
When a person is emotionally charged, stress could be discerned in his voice. This paper presents a simplified and a non-invasive approach to detect psycho-physiological stress by monitoring the acoustic modifications during a stressful conversation. Voice database consists of audio clips from eight different popular FM broadcasts wherein the host of the show vexes the subjects who are otherwise unaware of the charade. The audio clips are obtained from real-life stressful conversations (no simulated emotions). Analysis is done using PRAAT software to evaluate mean fundamental frequency (F0) and formant frequencies (F1, F2, F3, F4) both in neutral and stressed state. Results suggest that F0 increases with stress; however, formant frequency decreases with stress. Comparison of Fourier and chirp spectra of short vowel segment shows that for relaxed speech, the two spectra are similar; however, for stressed speech, they differ in the high frequency range due to increased pitch modulation.
