Advanced Technologies for Skill Enhancement and Talent Recognition

Abstract

Children with Down Syndrome encounter significant challenges in speech articulation, cognitive development and learning, which conventional educational approaches often struggle to address effectively. Difficulties in speech clarity, working memory and problem-solving highlight the need for adaptive learning solutions tailored to their unique needs. To address these challenges, EnlightenDS developed an artificial Intelligence system combined with educational technology that enhances learning through detection, pronunciation training, mathematics exercises and talent identification. The early detection of developmental concerns, facilitating timely intervention and module leverages support vector machine to assess the detection of Down Syndrome. The pronunciation training component integrates natural language processing and a flask-based API to process speech input, utilising google speech-to-text API and DeepSpeech AI for pronunciation evaluation. Speech-to-text conversion and phoneme-level articulation analysis further refine speech feedback. The mathematics training module applies structured learning methodologies like Kumon, Stern, and Numicon, ensuring an adaptive learning experience. Additionally, the talent identification system employs AI-driven implementation and machine learning based analysis to monitor engagement in learning, drawing, and motor activities, recognizing each child's talents and interests. Evaluation of EnlightenDS demonstrates that AI-powered assessment and personalised learning techniques significantly improve cognitive abilities and speech development while creating a more engaging educational experience. These findings emphasize the potential of AI, image processing and adaptive learning methodologies in special education, fostering enhanced communication, cognitive growth and talent recognition for children with Down Syndrome.