Performance evaluation of a voice-based depression assessment system considering the number and type of input utterances

Masakazu Higuchi, Noriaki Sonota, Mitsuteru Nakamura, Kenji Miyazaki, Shuji Shinohara, Yasuhiro Omiya, Takeshi Takano, Shunji Mitsuyoshi, Shinichi Tokuno

Research output: Contribution to journalArticlepeer-review

Abstract

It is empirically known that mood changes affect facial expressions and voices. In this study, the authors have focused on the voice to develop a method for estimating depression in individuals from their voices. A short input voice is ideal for applying the proposed method to a wide range of applications. Therefore, we evaluated this method using multiple input utterances while assuming a unit utterance input. The experimental results revealed that depressive states could be estimated with sufficient accuracy using the smallest number of utterances when positive utterances were included in three to four input utterances.

Original languageEnglish (US)
Article number67
JournalSensors
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2022
Externally publishedYes

Keywords

  • Mental health
  • Mood change by positive utterances
  • Voice biomarker

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Performance evaluation of a voice-based depression assessment system considering the number and type of input utterances'. Together they form a unique fingerprint.

Cite this