Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental and neurological disorder related to brain development, leading to problems of social communication and interaction. While there is no cure for ASD, effective and early interventions can improve its symptoms. Hence screening this problem from early ages is very important. In our research, speech of children and machine learning are used to classify children with ASD from typically developing ones. Obtained results show that the combination of speech features and k-Nearest Neighbor model is a promising approach for early detection of ASD.
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Cong-Phuong, N. (2024). Classification of Children with/without Autism Spectrum Disorder Using Speech Signal. In: Su, R., Zhang, YD., Frangi, A.F. (eds) Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023). MICAD 2023. Lecture Notes in Electrical Engineering, vol 1166. Springer, Singapore. https://doi.org/10.1007/978-981-97-1335-6_20
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DOI: https://doi.org/10.1007/978-981-97-1335-6_20
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