An attempt to estimate depressive status from voice

Yasuhiro Omiya, Takeshi Takano, Tomotaka Uraguchi, Mitsuteru Nakamura, Masakazu Higuchi, Shuji Shinohara, Shunji Mitsuyoshi, Mirai So, Shinichi Tokuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publicationPervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings
EditorsPietro Cipresso, Silvia Serino, Daniela Villani
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783030258719
StatePublished - 2019
Externally publishedYes
Event9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019 - Buenos Aires, Argentina
Duration: Apr 23 2019Apr 24 2019

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
ISSN (Print)1867-8211


Conference9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019
CityBuenos Aires


  • Depressive status estimation
  • The Hamilton Depression Rating Scale (HAM-D)
  • Vocal analysis

ASJC Scopus subject areas

  • Computer Networks and Communications


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