An Attempt to Estimate Depressive Status from Voice
In the whole world especially developed countries, increasing mental health disorders is a serious problem. As a countermeasure, the main objective of this paper is an attempt to estimate depressive status from voice. In this study, we gathered patients with major depressive disorders in the hospital’s consulting room. Several questionnaires including “the Hamilton Depression Rating Scale” (HAM-D) were administered to evaluate the patients’ depressed state. Voices corresponding to three long vowels were recorded from the subjects. Next, the acoustic feature quantity was calculated based on the voice. We developed the HAM-D score estimation algorithm from the voice using one of three types of long vowel audio content. As a result, there was a correlation between the “Actual HAM-D Score” and the “Estimated HAM-D Score”. We found that the algorithm is effective in estimating depression state and can be used for estimating the disease state based on voice.
KeywordsVocal analysis Depressive status estimation The Hamilton Depression Rating Scale (HAM-D)
- 1.Hamilton, M.: Rating depressive patients. J. Clin. Psychiatry 41, 21–24 (1980)Google Scholar
- 7.Sekiyama, A.: Interleukin-18 is involved in alteration of hipothalamic-pituitary-adrenal axis activity by stress. In: Society of Biological Psychiatry Annual Meeting, San Diego, USA (2007)Google Scholar
- 8.Kawamura, N., Shinoda, K., Ohashi, Y., Ishikawa, T., Sato, H.: Biomarker for depression, method for measuring a biomarker for depression, computer program, and recording medium. U. S. Patent, US2015126623 (2015)Google Scholar
- 12.Sheehan, D.V., et al.: The Mini-International Neuropsychiatric Interview (M.I.N.I): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59(Suppl. 20), 22–33 (1998)Google Scholar
- 13.Eyben, F., Wöllmer, M., Schuller, B.: Opensmile: the munich versatile and fast open-source audio feature extractor. In: Bimbo, A.D., Chang, S.F., Smeulders, A.W.M. (eds.) ACM Multimedia, pp. 1459–1462 (2010)Google Scholar