Computer tools in mental disorders diagnostics by oral speech

P. 147–157.

Khomenko A., Komratova A., Isakov D., Balba D., Shishkovskaya T., Khudyakova M.

The integration of automated speech analysis in diagnosing mental health disorders is becoming increasingly significant in both clinical and computational linguistics. This study aims to construct linguistic profiles for individuals with neurocognitive and affective mental disorders. Using speech transcriptions and relevant to the study computational techniques like lexical clustering and stylostatistical analysis, this research looks for characteristics capable of distinguishing speech patterns indicative of various mental health conditions. A text corpus of oral speech from 136 people diagnosed with schizophrenia, schizotypal disorder, schizoaffective disorder, borderline personality disorder, other personality disorders, primary depressive episode, recurrent depressive disorder, bipolar affective disorder and 210 participants with no diagnosed diseases in the control group was used in the research. As a result of the study, it was proved that people with mental disorders display specific features in oral speech, that can be used in creation of an automatic mental disorders diagnostic model.

Keywords: кластеризация, устная речь, mental disorders, oral speech, early automatic diagnostics, ментальные расстройства, ранняя автоматическая диагностика, стилостатистика, clustering, stylistics

Publication based on the results of: Neural foundations of language and its impairments: From basic research to clinical practice (2025)

In book

Computational linguistics and intellectual technologies. Papers from the Annual International Conference "Dialogue" (2025)

Vol. 23. , [б.и.], 2025.