Second International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2001)
Among the many clinical decisions that psychiatrists must make, assessment of a patient's risk of committing suicide is definitely among the most important, complex and demanding. One of the authors reviewing his clinical experience observed that successful predictions of suicidality were often based on the patient's voice independent of content. The voices of suicidal patients exhibited unique qualities, which distinguished them from non-suicidal patients. In this study we investigated the discriminating power of lower order mel-cepstral coefficients among suicidal, major depressed, and nonsuicidal patients. Our sample consisted of 10 near-term suicidal patients, 10 major depressed patients, and 10 non-depressed control subjects. Multivariate Gaussian mixtures using the first four mel-cepstral coefficients and six component functions were employed to model the class distributions of the extracted features. Maximum likelihood classification analyses of the groups yielded exceptional classification performance. Correct classification scores were: 80% between near-term suicidal patients and non-depressed controls, 75% between depressed patients and non-depressed controls, and 80% between nearterm suicidal patients and depressed patients.
Index Terms. suicide, speech, classification, mel-cepstrum
Bibliographic reference. Ozdas, Asli / Shiavi, Richard G. / Wilkes, D. Mitchell / Silverman, Marilyn K. / Silverman, Stephen E. (2001): "Analysis of vocal tract characteristics for near-term suicidal risk assessment", In MAVEBA-2001, 99-102.