Deep learning-based automated speech detection as a marker of social functioning in late-life depression

Roisin Mcnaney, Bethany Little*, Ossama Alshabrawy, Daniel Stow, Daniel Jackson, Karim Ladha, Nicol Ferrier, Cassim Ladha, Thomas Ploetz, Juame Bacardit, Patrick Olivier, Peter Gallagher, John O'Brien

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Background. Late-life depression (LLD) is associated with poor social functioning. However,
previous research uses bias-prone self-report scales to measure social functioning and a more
objective measure is lacking. We tested a novel wearable device to measure speech that participants encounter as an indicator of social interaction.
Methods. Twenty nine participants with LLD and 29 age-matched controls wore a wrist-worn
device continuously for seven days, which recorded their acoustic environment. Acoustic data
were automatically analysed using deep learning models that had been developed and validated on an independent speech dataset. Total speech activity and the proportion of speech
produced by the device wearer were both detected whilst maintaining participants’ privacy.
Participants underwent a neuropsychological test battery and clinical and self-report scales
to measure severity of depression, general and social functioning.
Results. Compared to controls, participants with LLD showed poorer self-reported social and
general functioning. Total speech activity was much lower for participants with LLD than
controls, with no overlap between groups. The proportion of speech produced by the participants was smaller for LLD than controls. In LLD, both speech measures correlated with attention and psychomotor speed performance but not with depression severity or self-reported
social functioning.
Conclusions. Using this device, LLD was associated with lower levels of speech than controls
and speech activity was related to psychomotor retardation. We have demonstrated that
speech activity measured by wearable technology differentiated LLD from controls with
high precision and, in this study, provided an objective measure of an aspect of real-world
social functioning in LLD.
Original languageEnglish
Pages (from-to)1-10
JournalPsychological Medicine
DOIs
Publication statusPublished - 16 Jan 2020

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