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Speech carries essential information about the speaker’s physiology and possible pathophysiological conditions. Bio-acoustic voice qualities show promising value for characterizing mood disorders. Depression alters several bio-acoustic features of speech, and by measuring and analyzing those, conventional diagnostic tools could be enhanced, and clinical support improved. Here, we review the use of speech as an objective biomarker of depression. We briefly review the speech production process and acoustic theory of voice production, and explore the most commonly quantified bio-acoustic characteristics and their correlation with depression. We highlight the effect of depression on speech production and bio-acoustic speech characteristics and conclude with a summary of speech-based studies that suggest that depression diagnostics could be augmented by speech. Advances in computerized speech processing allow for an objective analysis of speech and the classification of speakers’ conditions through machine learning. Encouraging early results suggest a future role for depression screening in the clinic.
Almaghrabi et al. (2023) studied this question.