Identification and classification of schizophrenic speech using convolutional neural network for medical healthcare
by Akshita Abrol; Nisha Kapoor; Parveen Kumar Lehana
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 15, No. 6, 2023

Abstract: Schizophrenia is a brain disorder that significantly affects the quality of life of affected individuals. One of its prominent symptoms is the induction of changes in the acoustics of the patients. In the absence of definite methods for its diagnosis, speech analysis can help in the preliminary screening of the patients. In this paper, an automated method using deep learning for differentiating between individuals with schizophrenia and psychosis from healthy individuals is suggested. Using convolutional neural networks with speech spectrograms as input, a classification accuracy of 87.01% has been obtained for levels of schizophrenia and 95.26% for differentiating between schizophrenic and healthy speech.

Online publication date: Fri, 27-Oct-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Medical Engineering and Informatics (IJMEI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com