Prediction of Social Maladaptation using Emotional Entrainment of Disgust during Comprehensive Psychiatric Interviews

Yokotani Kenji, Takagi Gen, Wakashima Kobun

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

Abstract

Previous speech entrainment studies have shown disagreement in their findings: One group emphasized that acoustic entrainment predicts social adaptation, whereas another group emphasized that it predicts social maladaptation. Our study aims to resolve the disagreement from the perspective of emotional entrainment: the entrainment of positive emotions predicts social adaptation, whereas the entrainment of negative emotions predicts social maladaptation. Using a machine-learned sentiment classifier, we estimated the probability of anger, disgust, fear, happiness, neutrality, and sadness in speech. The corpus consisted of dialogues recorded from 29 comprehensive mental health interviews. The Jensen- Shannon divergence was also calculated to estimate the (dis)entrainment. Results showed that the entrainment of happiness significantly demonstrated the rapport of the participants with their therapist. In contrast, their entrainment of disgust significantly demonstrated their social maladaptation. Our study observed social maladaptation to be contrastingly related to positive and negative emotional entrainment. Classification of speech from an emotional perspective could enrich the study of entrainment and facilitate the analysis of emotional communication.

Original languageEnglish
Title of host publication2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1001-1007
Number of pages7
ISBN (Electronic)9789881476883
Publication statusPublished - 2020 Dec 7
Event2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Virtual, Auckland, New Zealand
Duration: 2020 Dec 72020 Dec 10

Publication series

Name2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings

Conference

Conference2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020
CountryNew Zealand
CityVirtual, Auckland
Period20/12/720/12/10

Keywords

  • acoustic synchrony
  • comprehensive mental health interview
  • emotional entrainment
  • machine-learned sentiment classifier

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Instrumentation

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