Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.

Journal: BMC psychiatry
PMID: 40340671

Abstract

BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences and the heterogeneity of the disorder. In this study, a discriminative model of schizophrenic speech based on deep learning is developed, which combines different emotional stimuli and features.

Authors

  • Jie Huang
    Department of Critical Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • YanLi Zhao
    Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650200, China.
  • Zhanxiao Tian
    Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Changping District, Beijing, 100096, China.
  • Wei Qu
  • Xia Du
    Department of Nephrology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China.
  • Jie Zhang
    College of Physical Education and Health, Linyi University, Linyi, Shandong, China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Yunlong Tan
    Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China.
  • Zhiren Wang
    Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China.
  • Shuping Tan
    Psychiatry Research Center, Peking University Huilonguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China.

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