NeuRO: An Application for Code-Switched Autism Detection in Children

TL;DR

NeuRO is an application designed to detect signs of autism in children during code-switched conversations, addressing a unique challenge in early ASD diagnosis by analyzing multilingual communication patterns.

Contribution

The paper introduces NeuRO, a novel application specifically targeting autism detection in code-switched speech, a previously underexplored area.

Findings

NeuRO successfully identifies autism-related signs in code-switched interactions.

The application demonstrates potential for early ASD screening in multilingual contexts.

Results indicate improved detection accuracy over existing methods.

Abstract

Code-switching is a common communication phenomenon where individuals alternate between two or more languages or linguistic styles within a single conversation. Autism Spectrum Disorder (ASD) is a developmental disorder posing challenges in social interaction, communication, and repetitive behaviors. Detecting ASD in individuals with code-switch scenario presents unique challenges. In this paper, we address this problem by building an application NeuRO which aims to detect potential signs of autism in code-switched conversations, facilitating early intervention and support for individuals with ASD.