Voice Acoustic Parameters as Predictors of Depression

• Published in: Journal of voice Vol. 38; no. 1; pp. 77 - 85
• Main Authors: Silva, Wegina Jordana, Lopes, Leonardo, Galdino, Melyssa Kellyane Cavalcanti, Almeida, Anna Alice
• Format: Journal Article
• Language: English
• Published: United States 01.01.2024
• Subjects: Acoustics; Antidepressive Agents; Case-Control Studies; Depression - diagnosis; Humans; Speech Acoustics; Speech Production Measurement; Voice; Voice Quality; Depression; Voice disorders; Voice; Mental health; Speech acoustics
• DOI: 10.1016/j.jvoice.2021.06.018
• ISSN: 0892-1997

To analyze whether voice acoustic parameters are discriminant and predictive in patients with and without depression. Observational case-control study. The following instruments were administered to the participants: Self-Reporting Questionnaire (SRQ-20), Beck Depression Inventory-Second Edition (BDI-II), Voice Symptom Scale (VoiSS) and voice collection for subsequent extraction of the following acoustic parameters: mean, mode and standard deviation (SD) of the fundamental frequency (F0); jitter; shimmer; glottal to noise excitation ratio (GNE); cepstral peak prominence-smoothed (CPPS); and spectral tilt. A total of 144 individuals participated in the study: 54 patients diagnosed with depression (case group) and 90 without a diagnosis of depression (control group). The means of the acoustic parameters showed differences between the groups: F0 (SD), jitter, and shimmer values were high, while values for GNE, CPPS and spectral tilt were lower in the case group than in the control group. There was a significant association between BDI-II and jitter, shimmer, CPPS, and spectral tilt and between CPPS and the class of antidepressants used. The multiple linear regression model showed that jitter and CPPS were predictors of depression, as measured by the BDI-II. Acoustic parameters were able to discriminate between patients with and without depression and were associated with BDI-II scores. The class of antidepressants used was associated with CPPS, and the jitter and CPPS parameters were able to predict the presence of depression, as measured by the BDI-II clinical score.