Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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2018 - 20205

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Subject: search.filters.subject.Dyslexia

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Now showing 1 - 5 of 5
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    Pubudu: Deep learning based screening and intervention of dyslexia, dysgraphia and dyscalculia
    (IEEE, 2019-12-18) Kariyawasam, R; Nadeeshani, M; Hamid, T; Subasinghe, I; Samarasinghe, P; Ratnayake, p
    Dyslexia, Dysgraphia and Dyscalculia are significant learning disabilities that affect around 10% of children in the world. Despite the advancement of technology literacy in the community, limited attention has been given for screening and intervention of these disabilities using mobile applications in Sri Lanka. In this research, one of the first deep learning and machine learning based mobile applications, named “Pubudu” was developed for screening and intervention of dyslexia, dysgraphia and dyscalculia supporting local languages. In “Pubudu” we have followed up clinical screening and diagnostic procedures recommended by health professionals for screening and intervention. The screening of dyslexia, letter dysgraphia and numeric dysgraphia was carried out using deep neural network and the screening for dyscalculia was carried out using machine learning techniques. Intervention techniques are implemented using gamified environments. System testing was carried out using 50 differently abled children and 50 typical children. With the initial dataset 88%, 58%, 99% screening accuracies are achieved in neural networks for letter dysgraphia, dyslexia and numeric dysgraphia screening while dysgraphia, whereas 90% accuracy was achieved for dyscalculia. Handwritten letters and numbers were fed as inputs to CNN model in letter dysgraphia and numeric dysgraphia while embedded audio clips of letter pronunciation were fed in to voice recognition CNN model in dyslexia. “Pubudu” shows significant potential for screening and intervention of dyslexia, dysgraphia and dyscalculia in local languages motivating children and interactively making them able and would be an enabling app for most of the underprivileged children in Sri Lanka.
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    Arunalu: Learning Ecosystem to Overcome Sinhala Reading Weakness due to Dyslexia
    (IEEE, 2020-12-10) Sandathara, L; Tissera, S; Sathsarani, R; Hapuarachchi, H; Thelijjagoda, S
    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.
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    The Hope: An Interactive Mobile Solution to Overcome the Writing, Reading and Speaking Weaknesses of Dyslexia
    (IEEE, 2019-08-19) Thelijjagoda, S; Chandrasiri, M; Hewathudalla, D; Ranasinghe, P; Wickramanayake, I
    Dyslexia is the most common disorder in the world that have weaknesses in writing, reading and speaking. As a well spread disorder there are several stages of Dyslexia that has to recognize before giving the treatments. The current treatment is known as “Speech Therapy” which is given by a doctor or a therapist in a hospital or in a special education unit. These weaknesses are more wide spread and effects one in five people in the world. Dyslexia also runs in families. It can be recognized in kindergarten but if not it will be a huge disadvantage and will cause difficulties for further studies when the victim grows up. The people who are suffering from Dyslexia are step aside of the society and most of them are not very social and not open to the society. Therefor the treatment has to be creative and unique in order to get it in to the user. This tool named “The Hope” assembles Dyslexia therapies in a graphical and creative way to present the user to make it more accurate. Key content of this research covers selecting the Dyslexia stage, load the therapies and detect gestures and voice. The end result will be mainly based on Artificial Intelligence, Virtual reality, Image processing and Voice recognition technologies. Whoever suffers from Dyslexia or anyone who is willing to improve their writing, reading and speaking skills can use “The Hope” with a parent or a guardian and can get a clear improvement by following the therapies that the application provides daily. Application will provide an appreciation and a reward system to motivate and encourage the user to use the application daily. Following the therapies daily will improve the user skills. This tool lets users easily recognize their writing, reading and speaking weaknesses and will help to overcome them in a creative and accurate way.
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    Mobile App to Support People with Dyslexia and Dysgraphia
    (IEEE, 2018-12-21) Avishka, I; Kumarawadu, K; Kudagama, A; Weerathunga, M; Thelijjagoda, S
    Computers and technology play a very important role in human lives. Even though this statement is true, one can come in to a conclusion that there are many parts in the medical factor which are left untouched. The reason behind this is that each day various types of diseases that affect the human are found out. Dyslexia and dysgraphia have become trending disorders these days. It was found that 1 out of 10 people are having dyslexia adding up to 700 million people worldwide. 5-20 percent of people are facing problems with their handwriting mainly due to dysgraphia. People also have primary dyslexia which is caused from inheritance from their parents. The only treatment found out for patients diagnosed with dyslexia and dysgraphia are making them practice reading and writing until they reach a level fluency and accuracy. These patients face a lot of difficulties and obstacles such as channeling health professionals which can be very costly. Introducing a mobile application known as “The CURE” which helps the patients to practice reading and writing on their own. This paper describes about the system which helps to identify and evaluate whether a normal person is having dyslexia and dysgraphia and if so to help them to practice reading and letter writing. Two machine learning models are trained for two different data sets to increase the accuracy and reliability of the system. One model will be used to identify the words that are spelled out by the dyslexic patient and the other to identify the characters written by the patient diagnosed with dysgraphia. The application is built in an interactive manner to keep the user interested with the system. With implementation of “The CURE” the number of patients diagnosed with dyslexia and dysgraphia will reduce drastically with minimum assistance from health professionals.
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    Arunalu: Learning Ecosystem to Overcome Sinhala Reading Weakness due to Dyslexia
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Sandathara, L.; Tissera, S.; Sathsarani, R.; Hapuarachchi, H.; Thelijjagoda, S.
    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.