Voice analysis can help measure the diagnosis, severity, and onset of mental illness

microphone on the table

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Objectively measuring mental disorders has long proved difficult. However, there is ample evidence that analyzing speech patterns can accurately diagnose depression and psychosis, measure their severity and predict their onset, according to a review. material published in the January/February issue of the magazine Harvard Journal of Psychiatry.

The review reviewed the current published literature regarding the use of speech pattern analysis for the management of psychiatric disorders and identified four key application areas: diagnostic classification, severity assessment severity, predictive of onset, as well as prognosis and treatment outcome. “Models that aggregate multiple speech features can distinguish speakers from psychosis from healthy controls with high precision,” said Rudolf Uher, Ph.D., MD, Dalhousie University Department of Psychiatry and Nova Scotia Health, and colleagues Katerina Dikaios, MS, Sheri Rempel, MS , Sri Harsha Dumpala, MSc, Sageev Oore, Ph.D., and Michael Kiefte, Ph.D.

Automated analysis is more promising than subjective measures like interviews or questionnaires

features of mental illness are often expressed through speech and language, and clinical psychiatric evaluation should consider patterns in the patient’s speech—such as speed, coherence, and content. Progress in natural language processing, voice recognitionand computer science have highlighted the fact that speech analysis can be used as an objective, clinical measure of mental illness.

The research team reviewed hundreds of articles, articles and reports by people with mental disorders discussing aspects of their speech. Case studies and studies of patients with neurological disorders were excluded from the review. These included articles that analyzed the transcription of participants’ speech.

Most of the studies included in the review discussed the use of speech analysis in the diagnosis of patients with severe depression, whose speech is often slow, full of interruptions, negative content, and lacks energy. In which, the diagnostic accuracy is high, more than 80% in one study.

Automated analysis is also effective in predicting the onset of mental illness, especially in high-risk groups. Many studies looking at the semantics of speech, including coherence and complexity, have predicted the onset of psychosis after two to two and a half years with up to 100% accuracy. However, the literature on the impact of speech analysis on prognosis and treatment outcomes is limited and requires further study.

Importantly, the use of speech pattern analysis in the assessment of suicide risk appears to have great potential. A recent study found that measuring variables such as frequency of erratic behavior, hesitancy, and restlessness identified patients with suicidal ideation compared with healthy patients in 73% of cases.

Verbal variance, other problems remain

Many factors, such as drug effects, as well as demographic and cultural attributes—language, sex, and gender, among others—can cause differences in how speak and make matching difficult. stated become objective disease and evaluate the results. In addition, the authors suggest that any further studies should look at disease status over time, as most of the studies examined here looked at patients who are currently more ill. is whether similar patterns persist long-term between symptoms.

More information:
Katerina Dikaios et al, Applications of speech analysis in psychiatry, Harvard Journal of Psychiatry (2023). DOI: 10.1097/HRP.0000000000000356

quote: Speech analysis can help assess the diagnosis, severity, and onset of mental illness (2023, January 6) retrieved January 9, 2023 from /news/2023-01-speech-analysis-diagnosis-severity-onset. html

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