Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning
Speech analysis under neutral emotional stimulation demonstrated greater differences between schizophrenia patients and healthy controls, enhancing discriminative analysis of schizophrenia. Integrating different emotions, demographic information and MFCCs improved the accuracy of schizophrenia detection. This study provides a methodological foundation for constructing a personalized speech detection model for schizophrenia.
Authors
- Wei Qu (ORCID: https://orcid.org/0000-0002-8507-592X)
- Zhiren Wang (ORCID: https://orcid.org/0000-0002-2016-0517)
- Shuping Tan (ORCID: https://orcid.org/0000-0002-1265-5093)
- Yunlong Tan (ORCID: https://orcid.org/0000-0002-3522-3912)
- Zhanxiao Tian
- Xia Du (ORCID: https://orcid.org/0000-0002-6474-6579)
- Jie M. Zhang (ORCID: https://orcid.org/0000-0003-0481-7264)
- Jie Huang (ORCID: https://orcid.org/0000-0002-6753-8679)
- Meng Zhang (ORCID: https://orcid.org/0000-0003-1465-9714)
- Yanli Zhao (ORCID: https://orcid.org/0000-0001-9188-1138)
Institutions
- Beijing HuiLongGuan Hospital (CN)
Publication Details
- Journal
- BMC Psychiatry
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s12888-025-06888-z
- Citations
- 4
- Primary Topic
- Music and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 5.94
Funders
- Beijing Municipal Science and Technology Commission