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- W4285246937 abstract "Autism Spectrum Disorder is a neurological disorder which affects the emotional, cognitive, social and physical health of the individual. Symptoms involve trouble in communication, difficulty in social interactions, obsession and repetitive behaviors. Identifying ASD at early age is important to reduce the effects of disorder through behavioral, educational and family therapies. Artificial Intelligence has played a significant role in identifying ASD in children. This research presents a new approach to identify ASD through emotion in children through video and audio using Artificial Neural Network. Model is trained using Convolutional Neural Network to detect facial emotion on images of autistic and non-autistic children and further use to generate emotion features. Speech Emotion Recognition is trained to predict the emotion of the child and get speech and emotion features. Face and speech emotion features are trained using supervised algorithms to predict ASD. Logistic Regression outperforms the other model with an F1 Score of 0.70 for Non ASD and 0.60 for ASD." @default.
- W4285246937 created "2022-07-14" @default.
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- W4285246937 date "2022-01-01" @default.
- W4285246937 modified "2023-10-17" @default.
- W4285246937 title "Multimodal Autism Detection in Children Through Facial and Speech Emotion" @default.
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- W4285246937 doi "https://doi.org/10.1007/978-981-19-1122-4_71" @default.
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