Faculty of Computing

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Author: search.filters.author.Alosius, J.

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    Learning Assistant To Acquire The Fundamental Language Skills for Non-Native Learners Using AI
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Srikanthan, P.; Nizar, R.; Ravikumar, A.; Lalitharan, K.; Harshanath, S.M.B.; Alosius, J.
    The ability to speak and learn a language properly requires good practice, experience and good learning strategies but the existing solutions do not provide proper guidance to learn a language with instant feedback. This research is an approach to devise an improved language learning assistant with practices that will help to improve the fundamental language skills for non-native learners and children who are in the early stage of their education. The four main skills focused on this application will be conversation, pronunciation, listening and grammatical skills. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The solution of this research is delivered by using a cross-platform application called GLIB which facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language.
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    Gamified Smart Mirror 􀁗o Leverage Autistic Education – Aliza
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Najeeb, R.S.; Uthayan, J.; Lojini, R.P.; Vishaliney, G.; Alosius, J.; Gamage, A.
    Autism is a neurodevelopmental disorder that causes difficulties in communication, emotional responsiveness and social skills. There has been a global increase rate in autism and lack of resources locally to educate ASD children. As this condition affects children at an early stage, it remains a challenge in learning. Even though today's world there are ample of teaching methods and technologies, people are unaware of the use and impact of them. This paper presents “Aliza” Gamified smart mirror to teach basic education for autism children. “Aliza” consists of four core components such as writing mentor for pre-writing, math tutor for mathematics, verbal trainer for speech and attentiveness tracker for emotion detection. These components assist and enhance their competency in education. The users of the “Aliza" will be constantly monitored and evaluated during their training using Convolutional Neural Network (CNN). The interactive games are given to impact their learning process while the generated report from the Deep Learning evaluation system can acquaint parents and the tutors with the progress of the children. Through this research, it is expected to improve autistic children's basic education with assistance of “Aliza".