Browsing by Author "Vidanaralage, A. J"

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Huruwa: An AI-IoT Robotic System for Adaptive Speech Therapy and Parental Support for Sinhala-Speaking Children with Speech Sound Disorders
(Institute of Electrical and Electronics Engineers Inc., 2026-05-21) Iddamalgoda, R; Piyathilaka, D; Pallebathgala, D; Abeyrathne, H; Thelijjagoda, S; Vidanaralage, A. J
Early phonological intervention for Sinhalaspeaking children with speech sound disorders requires scalable, engaging tools that bridge clinical expertise and home practice; however, low-resource language constraints limit available solutions. This paper introduces Huruwa, an AI-IoT robotic platform designed to support speech therapy for Sinhala-speaking children. The system integrates LLM-guided conversational interaction, phoneme-adaptive exercises (80-90% task suitability), and SVM-RBF-based phoneme error detection achieving 78% accuracy. It further employs knowledge-graph-driven therapy generation and a RAG-based parent guidance system to deliver grounded, hallucination-controlled support. Evaluations confirm real-time feasibility across components, offering a deployable model for Sinhala child speech therapy in resource-limited settings like Sri Lanka.
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LexAyudha : Personalized AI-Driven Rehabilitation for Adolescents with Dyslexia and Dyscalculia
(Institute of Electrical and Electronics Engineers Inc., 2025-07-03) Silva, U; Madusanka, I; Thalangama, T; Dissanayake, T; Thelijjagoda, S; Vidanaralage, A. J
Dyslexia and dyscalculia, the most common learning disabilities, produce a considerably challenging environment for adolescents and lead to frustration, disengagement, and reduced self-esteem. While assistive technologies with influential functionalities exist, they lack personalization for effective and supportive learning. LexAyudha is an AI-powered platform addressing these gaps by integrating proven medical methodologies such as chromatic variation, Touch Math, and multisensory teaching strategies. Advanced AI technologies like Convolutional and Recurrent Neural Networks have been used in LexAyudha to dynamically adjust reading content, visual layouts, and lesson plans in the gamified app based on students' performances to cater for their requirements. Moreover, a novel emotion recognition algorithm even adjusts difficulty levels of activities and voice output with altered audio features to ensure a stress-free learning process and a stimulating environment. Initial findings based on the user performances tests conducted with the dyslexic and dyscalculia adolescents in Sri Lanka, represents significant improvements in reading fluency, comprehension, and motivation, showing that adaptive learning with AI has the potential to revolutionize learning for dyslexic and dyscalculia students. The research identifies the potential of rehabilitation with AI-driven technology as a flexible and scalable solution for personalized education in dyslexia and dyscalculia.
Embargo
Sinhala language decoder
(IEEE, 2018-10-02) Vidanaralage, A. J; Illangakoon, A. U; Sumanaweera, S. Y; Pavithra, C; Thelijjagoda, S
The purpose of this paper is to present a Sinhala and English bilingual translator to overcome language barrier which prevails in Sri Lankan organizations when collaborating business across international boundaries. First phase of the research involves statistically analyzing relationships and validating the semantic meaning between Sinhala and English sentences. Next phase is to develop Singlish transliteration approach to render Sinhala words typed using English. Final phase of the study involves recognizing handwritten Sinhala characters used in modern literature within an acceptable accuracy. The anticipated outcome is to improve communication effectiveness when doing business and to minimize time, cost, and human errors caused by a human translator.