Speech and Voice Quality as Digital Biomarkers in Depression: A Systematic Review.

[en] [en] OBJECTIVE: To review the current evidence on the use of artificial intelligence-driven speech and voice analysis as a biomarker for depression. METHODS: PubMed, Scopus, and Cochrane databases were reviewed by two independent investigators for studies investigating the use of artificial intelligence-driven speech and voice quality outcomes as biomarkers for depression according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements. The methodological quality and risk of bias of each included study were assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. RESULTS: Of the 108 identified records, 12 studies met the inclusion criteria. The studies examined 16 872 participants, including patients with major depressive disorder (n = 1535), bipolar disorder (n = 111), schizophrenia spectrum disorders (n = 35), and anxiety disorders (n = 224). Control groups included a total of 1204 healthy individuals. Speech and voice quality outcomes consistently distinguished depression from controls (AUC = 0.71-0.93), with prosodic, spectral, and perturbation measures showing significant correlations with standardized depression scales. Classification accuracies ranged from 78% to 96.5%. Six studies demonstrated high risk of methodological bias, primarily in patient selection and validation techniques. Voice recording contexts varied between clinical settings and mobile technologies. CONCLUSION: The findings of this review highlight the potential of voice biomarkers as a novel tool for depression detection and monitoring. While current evidence demonstrates promising classification accuracy, methodological heterogeneity and generalizability concerns must be addressed before widespread clinical adoption.

Disciplines :

Psychiatry
Otolaryngology

Author, co-author :

BRIGANTI, Giovanni ; Université de Mons - UMONS > Faculté de Médecine et de Pharmacie > Service de Médecine computationnelle et Neuropsychiatrie

Lechien, Jérome ; Université de Mons - UMONS > Faculté de Psychologie et des Sciences de l'Education > Service de Métrologie et Sciences du langage ; Université de Mons - UMONS > Faculté de Médecine, Pharmacie et Sciences Biomédicales > Service de Chirurgie ; Université de Mons - UMONS > Faculté de Médecine et de Pharmacie > Service de Chirurgie

Language :

English

Title :

Speech and Voice Quality as Digital Biomarkers in Depression: A Systematic Review.

Publication date :

22 May 2025

Journal title :

Journal of Voice

ISSN :

0892-1997

eISSN :

1873-4588

Publisher :

Elsevier BV, United States

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0892199725001870?httpAccept=text/xml

Research unit :

M120 - Service de Chirurgie
M121 - Service de Médecine computationnelle et Neuropsychiatrie

Research institute :

Santé

Available on ORBi UMONS :

since 17 October 2025

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