Arunalu: Learning Ecosystem to Overcome Sinhala Reading Weakness due to Dyslexia

Abstract

Dyslexia is an impairment in ability in reading. People having Dyslexia has difficulties in identifying specific letters and words and identifying speech sounds and decoding the letters which leads to difficulties in comprehension, spelling and writing. Dyslexia may severely affects language development and impacts reading and other language based improvement and functioning. “ARUNALU: Learning ecosystem to overcome reading disabilities in Sinhala language due to Dyslexia” has been proposed as a multi-sensory mobile solution, in native language of Sri Lanka (Sinhala) and with effective screening and intervention methodologies recommended by health professionals. Objective is to deliver, a phonological support to enhance reading skills of dyslexic children by providing a machine learning based automated screening and intervention mobile solution. Through these reading environments, there's a reward system in intervention process to encourage the user, and also users and respective parties can analyze user's progress. The proposed system is mainly based on Voice recognition, Natural Language Processing, Machine Learning and Deep Learning concepts collaborating with reading and gaming environments. Core Objective of the proposed system is to come up with a better and effective screening and intervention methodologies for early identification of Dyslexia and provide phonological training to overcome Sinhala reading difficulties due to Dyslexia in a user friendly manner.