Speech based suicide risk recognition for crisis intervention hotlines using explainable multi-task learning.

Journal: Journal of affective disorders
PMID: 39528146

Abstract

BACKGROUND: Crisis Intervention Hotline can effectively reduce suicide risk, but suffer from low connectivity rates and untimely crisis response. By integrating speech signals and deep learning to assist in crisis assessment, it is expected to enhanced the effectiveness of crisis intervention hotlines.

Authors

  • Zhong Ding
    Psychological Science and Health Research Center, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China; Institute of Education, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China; School of Automation, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China.
  • Yang Zhou
    State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, China.
  • An-Jie Dai
    School of Automation, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China.
  • Chen Qian
  • Bao-Liang Zhong
    Psychological Science and Health Research Center, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China; Wuhan Mental Health Center, Jianshe Avenue, Wuhan 430032, Hubei, China; Wuhan Hospital for Psychotherapy, Jianshe Avenue, Wuhan 430032, Hubei, China. Electronic address: haizhilan@gmail.com.
  • Chen-Ling Liu
    Psychological Science and Health Research Center, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China; Institute of Education, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China. Electronic address: liuchl@cug.edu.cn.
  • Zhen-Tao Liu
    Psychological Science and Health Research Center, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China; School of Automation, China University of Geosciences, Lumo Road, Wuhan 430074, Hubei, China. Electronic address: liuzhentao@cug.edu.cn.

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