LONGITUDINAL MODELING OF DEPRESSION SHIFTS USING SPEECH AND LANGUAGE

Perez Toro PA, Dineley J, Kaczkowska A, Conde P, Zhang Y, Matcham F, Siddi S, Haro JM, Bruce S, Wykes T, Bailón R, Vairavan S, Dobson RJ, Maier A, Nöth E, Orozco Arroyave JR, Narayan VA, Hotopf M, Cummins N (2024)

Publication Type: Conference contribution

Publication year: 2024

Journal

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 12021-12025

Conference Proceedings Title: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Event location: Seoul, KOR

ISBN: 9798350344851

DOI: 10.1109/ICASSP48485.2024.10447195

Abstract

Speech analysis can provide a potential non-invasive and objective means of assessing and monitoring an individual's mental health. Most studies to date have focused on cross-sectional analysis and have not explored the benefits of speech analysis as a longitudinal monitoring tool that can assist in the management of chronic conditions such as major depressive disorder (MDD). Objectively monitoring for shifts in depression symptom severity levels over time presents a notable challenge, which we address through an automated approach using longitudinal English and Spanish speech samples collected from a clinical population. We employ time-frequency representations and linguistic embeddings to enhance the early recognition of alterations in depression levels in individuals with MDD. We investigate the suitability of using siamese-based training for modeling these changes, intending to enable personalized and adaptive interventions.

Authors with CRIS profile

Involved external institutions

Janssen Global Services, LLC United States (USA) (US) King’s College London United Kingdom (GB) Universidad de Zaragoza Spain (ES) Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) Spain (ES) Davos Alzheimer's Collaborative United States (USA) (US)

How to cite

APA:

Perez Toro, P.A., Dineley, J., Kaczkowska, A., Conde, P., Zhang, Y., Matcham, F.,... Cummins, N. (2024). LONGITUDINAL MODELING OF DEPRESSION SHIFTS USING SPEECH AND LANGUAGE. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 12021-12025). Seoul, KOR: Institute of Electrical and Electronics Engineers Inc..

MLA:

Perez Toro, Paula Andrea, et al. "LONGITUDINAL MODELING OF DEPRESSION SHIFTS USING SPEECH AND LANGUAGE." Proceedings of the 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Seoul, KOR Institute of Electrical and Electronics Engineers Inc., 2024. 12021-12025.

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