Comprehensive Summary
This study explores the performance of speech emotion recognition (SER) technologies and how SER technologies have already been used in medicine - specifically in psychiatry. Researchers queried through the databases of PubMed, IEEE Xplore, arXiv, and ScienceDirect with the newest articles being published in February 2025. The Quality Assessment of Diagnostic Accuracy Studies tool was then used to measure the risk of bias. From the 14 articles reviewed, three addressed suicide risk, eight studied depression, and three discussed psychotic disorders. The review of SER technologies showed promising results in detecting emotional patterns linked to mental health disorders. Some of the studies also suggested that SER technologies could be used as a noninvasive tool to diagnose and monitor patients. In the discussion, the authors emphasize that although results from SER technologies are promising, its clinical usefulness is currently limited until models with real-world datasets are created.
Outcomes and Implications
This research is important as it explores ways that SER technology may be able to be used in the future to detect and monitor psychiatric conditions. SER methods may be more objective than traditional self- or clinician-report methods of assessment, thus may reduce bias. These technologies also have the potential to be used to tailor interventions based on individuals' unique features. Further development of this technology may ease some of the burden on clinicians by streamlining the process of diagnosing and monitoring patients.