Acoustic and language analysis of speech for suicidal ideation among US veterans

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Anas Belouali, Samir Gupta, Vaibhav Sourirajan, Jiawei Yu, Nathaniel Allen, Adil Alaoui, Mary Ann Dutton, Matthew J. Reinhard

Published: 2021, Last Modified: 06 Feb 2026BioData Min. 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Screening for suicidal ideation in high-risk groups such as U.S. veterans is crucial for early detection and suicide prevention. Currently, screening is based on clinical interviews or self-report measures. Both approaches rely on subjects to disclose their suicidal thoughts. Innovative approaches are necessary to develop objective and clinically applicable assessments. Speech has been investigated as an objective marker to understand various mental states including suicidal ideation. In this work, we developed a machine learning and natural language processing classifier based on speech markers to screen for suicidal ideation in US veterans.