Estimating Depressive Symptom Class from Voice
Authors:
- Takeshi TakanoTTTakeshi Takano
- Daisuke MizuguchiDMDaisuke Mizuguchi
- Yasuhiro OmiyaYOYasuhiro Omiya
- Masakazu HiguchiMHMasakazu Higuchi
- Mitsuteru NakamuraMNMitsuteru Nakamura
- Shuji ShinoharaSSShuji Shinohara
- Shunji MitsuyoshiSMShunji Mitsuyoshi
- Taku SaitoTSTaku Saito
- Aihide YoshinoAYAihide Yoshino
- Hiroyuki TodaHTHiroyuki Toda
- Shinichi TokunoSTShinichi Tokuno
Open Access
- 23 February 2023
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 20 (5) , 3965
Abstract
Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients’ distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in different symptom groups based on acoustic features of their speech. We could separate different symptom groups with an accuracy of 79%. The results suggest that voice from speech can estimate the symptoms associated with depression.Keywords
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