Speech pattern analysis can help diagnose, manage psychiatric disorders

Objective measurement of mental disorders has long proven difficult. Still, there is ample evidence that analysis of speech patterns can accurately diagnose depression and psychosis, measure their severity, and predict their onset. Harvard Review of PsychiatryThis journal is featured in Wolters Kluwer’s Lippincott Portfolio.

This review surveys the currently published literature relevant to the use of voice pattern analysis to manage psychiatric disorders and identifies four important application areas: diagnostic classification, severity assessment, onset prediction, prognosis and treatment outcome. has been identified. “A model that combines multiple speech features can distinguish between psychopathic speakers and healthy controls with high accuracy,” says Rudolf Uher, Ph.D., MD, and colleagues from Dalhousie University School of Psychiatry and Nova Scotia Department of Health. Katerina Dikaios MSc Sheri Rempel of MSc, Sri Harsha Dumpala, MSc, Sageev Oore, PhD, Michael Kiefte, PhD, January/February issue Harvard Review of Psychiatry.

Automated analysis holds promise over subjective measurements such as interviews and surveys

The hallmarks of psychiatric illness are often presented through speech and language, and psychiatric clinical assessments should consider the patient’s pattern of speech, including speed, coherence, and content. Advances in natural language processing, speech recognition, and computer science underscore the fact that clinical measurement of mental illness is possible using speech analysis as an objective tool.

The research team reviewed hundreds of articles, papers, and reports of individuals with mental disorders and discussed aspects of their speech. Case studies and studies of patients with neurological disorders were excluded from the review. They included articles that analyzed transcripts of participants’ speeches.

Most studies included in reviews discussing the use of voice analysis in diagnosis involved patients with major depression, whose speech was often slow, paused, negative in content, and lacked energy. I’m here. These diagnostic accuracies were high, over 80% in one study.

Automated analysis is also effective in predicting the development of psychiatric disorders, especially in high-risk populations. Studies examining speech semantics, such as coherence and complexity, predicted the onset of psychosis with 100% accuracy at 2 to 2.5 years. However, the literature on the impact of voice analysis on prognosis and treatment outcome is limited and further research is needed.

Importantly, the use of speech pattern analysis to assess suicide risk appears to have great potential. A recent study showed that measuring variables such as irregular frequency, hesitation, and jitter identified suicidal patients 73% of the time compared to healthy patients.

Speech distribution and other issues remain

A variety of factors, including drug influence, language, gender, and demographic and cultural attributes such as gender, lead to variability in speech patterns and make it difficult to incorporate speech into objective assessments of illness and outcome. increase. Furthermore, the authors note that most of the studies investigated here looked at currently ill patients rather than whether similar patterns persisted long-term between symptoms, so future studies should focus on disease status. It suggests that it should be considered over time.