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...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Jung Hyuk, Lee, Geon Woo, Bong, Guiyoung, Yoo, Hee Jeong, Kim, Hong Kook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823402/
https://www.ncbi.nlm.nih.gov/pubmed/36616801
http://dx.doi.org/10.3390/s23010202

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823402/
https://www.ncbi.nlm.nih.gov/pubmed/36616801
http://dx.doi.org/10.3390/s23010202

Ejemplares similares