2025/01/22 by Jimi Togni, Togni, Jimi
Computer Science · Health Professions · Medicine · #68T50 #Artificial Intelligence (cs.AI) #Audio and Speech Processing (eess.AS) #D.2.3 #Diverse Approaches in Healthcare and Education Studies #Education and Learning Interventions #FOS: Computer and information sciences #FOS: Electrical engineering #Human-Computer Interaction (cs.HC) #I.2.7 #Innovation in Digital Healthcare Systems #Machine Learning (cs.LG) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2503.15501
openalex publication_date 2025/01/22 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28
This study addresses the pressing challenge of educational inclusion for students with special needs by proposing and developing an inclusive educational platform. Integrating machine learning, natural language processing, and cross-platform interfaces, the platform features key functionalities such as speech recognition functionality to support voice commands and text generation via voice input; real-time object recognition using the YOLOv5 model, adapted for educational environments; Grapheme-to-Phoneme (G2P) conversion for Text-to-Speech systems using seq2seq models with attention, ensuring natural and fluent voice synthesis; and the development of a cross-platform mobile application in Flutter with on-device inference execution using TensorFlow Lite. The results demonstrated high accuracy, usability, and positive impact in educational scenarios, validating the proposal as an effective tool for educational inclusion. This project underscores the importance of open and accessible technologies in promoting inclusive and quality education.