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Performance Evaluation of a Voice-Based Depression Assessment System Considering the Number and Type of Input Utterances.

Masakazu HiguchiNoriaki SonotaMitsuteru NakamuraKenji MiyazakiShuji ShinoharaYasuhiro OmiyaTakeshi TakanoShunji MitsuyoshiShinichi Tokuno
Published in: Sensors (Basel, Switzerland) (2021)
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.
Keyphrases
  • sleep quality
  • depressive symptoms
  • bipolar disorder
  • stress induced