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

doi:10.1007/978-3-030-25872-6_13

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 proceeding › Conference contribution

Abstract

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 language	English (US)
Title of host publication	Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings
Editors	Pietro Cipresso, Silvia Serino, Daniela Villani
Publisher	Springer Verlag
Pages	168-175
Number of pages	8
ISBN (Print)	9783030258719
DOIs	https://doi.org/10.1007/978-3-030-25872-6_13
State	Published - 2019
Externally published	Yes
Event	9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019 - Buenos Aires, Argentina Duration: Apr 23 2019 → Apr 24 2019

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	288
ISSN (Print)	1867-8211

Conference

Conference	9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019
Country/Territory	Argentina
City	Buenos Aires
Period	4/23/19 → 4/24/19

Keywords

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

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1007/978-3-030-25872-6_13

Cite this

Omiya, Y., Takano, T., Uraguchi, T., Nakamura, M., Higuchi, M., Shinohara, S., Mitsuyoshi, S., So, M., & Tokuno, S. (2019). An attempt to estimate depressive status from voice. In P. Cipresso, S. Serino, & D. Villani (Eds.), Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings (pp. 168-175). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 288). Springer Verlag. https://doi.org/10.1007/978-3-030-25872-6_13

An attempt to estimate depressive status from voice. / Omiya, Yasuhiro; Takano, Takeshi; Uraguchi, Tomotaka; Nakamura, Mitsuteru; Higuchi, Masakazu; Shinohara, Shuji; Mitsuyoshi, Shunji; So, Mirai; Tokuno, Shinichi.

Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. ed. / Pietro Cipresso; Silvia Serino; Daniela Villani. Springer Verlag, 2019. p. 168-175 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 288).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Omiya, Y, Takano, T, Uraguchi, T, Nakamura, M, Higuchi, M, Shinohara, S, Mitsuyoshi, S, So, M & Tokuno, S 2019, An attempt to estimate depressive status from voice. in P Cipresso, S Serino & D Villani (eds), Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 288, Springer Verlag, pp. 168-175, 9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019, Buenos Aires, Argentina, 4/23/19. https://doi.org/10.1007/978-3-030-25872-6_13

Omiya Y, Takano T, Uraguchi T, Nakamura M, Higuchi M, Shinohara S et al. An attempt to estimate depressive status from voice. In Cipresso P, Serino S, Villani D, editors, Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. Springer Verlag. 2019. p. 168-175. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). https://doi.org/10.1007/978-3-030-25872-6_13

Omiya, Yasuhiro ; Takano, Takeshi ; Uraguchi, Tomotaka ; Nakamura, Mitsuteru ; Higuchi, Masakazu ; Shinohara, Shuji ; Mitsuyoshi, Shunji ; So, Mirai ; Tokuno, Shinichi. / An attempt to estimate depressive status from voice. Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings. editor / Pietro Cipresso ; Silvia Serino ; Daniela Villani. Springer Verlag, 2019. pp. 168-175 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

@inproceedings{47984924222a448485001eaebb8a39db,

title = "An attempt to estimate depressive status from voice",

abstract = "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{\textquoteright}s consulting room. Several questionnaires including “the Hamilton Depression Rating Scale” (HAM-D) were administered to evaluate the patients{\textquoteright} 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.",

keywords = "Depressive status estimation, The Hamilton Depression Rating Scale (HAM-D), Vocal analysis",

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

note = "Publisher Copyright: {\textcopyright} 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019 ; Conference date: 23-04-2019 Through 24-04-2019",

year = "2019",

doi = "10.1007/978-3-030-25872-6_13",

language = "English (US)",

isbn = "9783030258719",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Verlag",

pages = "168--175",

editor = "Pietro Cipresso and Silvia Serino and Daniela Villani",

booktitle = "Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings",

}

TY - GEN

T1 - An attempt to estimate depressive status from voice

AU - Omiya, Yasuhiro

AU - Takano, Takeshi

AU - Uraguchi, Tomotaka

AU - Nakamura, Mitsuteru

AU - Higuchi, Masakazu

AU - Shinohara, Shuji

AU - Mitsuyoshi, Shunji

AU - So, Mirai

AU - Tokuno, Shinichi

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Depressive status estimation

KW - The Hamilton Depression Rating Scale (HAM-D)

KW - Vocal analysis

UR - http://www.scopus.com/inward/record.url?scp=85069635044&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85069635044&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-25872-6_13

DO - 10.1007/978-3-030-25872-6_13

M3 - Conference contribution

AN - SCOPUS:85069635044

SN - 9783030258719

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 168

EP - 175

BT - Pervasive Computing Paradigms for Mental Health - 9th International Conference, MindCare 2019, Proceedings

A2 - Cipresso, Pietro

A2 - Serino, Silvia

A2 - Villani, Daniela

PB - Springer Verlag

T2 - 9th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2019

Y2 - 23 April 2019 through 24 April 2019

ER -

An attempt to estimate depressive status from voice

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this