End-to-End Model-Based Detection of Infants with Autism Spectrum Disorder Using a Pretrained Model

End-to-End Model-Based Detection of Infants with Autism Spectrum Disorder Using a Pretrained Model

In this paper, we propose an end-to-end (E2E) neural network model to detect autism spectrum disorder (ASD) from children’s voices without explicitly extracting the deterministic features. In order to obtain the decisions for discriminating between the voices of children with ASD and those with typi...

Full description

Bibliographic Details
Main Authors: Jung Hyuk Lee, Geon Woo Lee, Guiyoung Bong, Hee Jeong Yoo, Hong Kook Kim
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Sensors
Subjects:
autism spectrum disorder
end-to-end neural network
pretrained model
joint optimization
autoencoder
bidirectional long short-term memory (BLSTM)
Online Access:https://www.mdpi.com/1424-8220/23/1/202

Internet

https://www.mdpi.com/1424-8220/23/1/202

Similar Items