Research Publications
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Item Embargo Interactive Sinhala Letter Learning Module for School Children (Grade 1 to 5)(Springer Science and Business Media Deutschland GmbH, 2026) Weerasooriya, K; Udana, I; Jayasinghe, L; Kasiwaththa, J; Rajapaksha, S; Kumari, SSinhala is the native language of most people in Sri Lanka. However, most of the children find it difficult to write Sinhala letters fast and accurately, this may undermine their confidence and affect grades. The primary issue is that the parents usually lack their time in order to assist their children in their studying at home. Few interesting tools also exist to teach children how to write in Sinhala in an interesting and effective manner. To address these issues we have developed the ”Interactive Application of the Sinhala Language to School children (Grade 1 to 5) which is a web based application, to allow children studying in primary schools to enhance their knowledge of the Sinhala language. This app provides children an entertaining and effective method of learning how to write Sinhala letters. The system combines instructions in animation, touch tracing finger tools, hand writing recognition and immediate feedback such that kids can learn Sinhala writing, and the non touch screen users can post their written letters on paper to be analyzed individually as to feedback analysis. The system uses handwriting recognition to provide real-time feedback on accuracy and speed. The system also monitors progress and generates comprehensive reports to help children and parents in identifying areas requiring improvement. The application uses a combination of engaging letter tracing and intensive deep learning which are not present in other learning tools. Additionally, the system will aid parents to mentor their children in education even when they are in charged schedules and also enable children improve their skills in Sinhala writing. We offer to make the learning of Sinhala to school students in Sri Lanka easier, more relevant and interesting.Publication Embargo MiMi: Sinhala Language Speech Assistive Learning Bot to Support Children with Stuttering(IEEE, 2022-12-13) Vithana, K.C.D; Weerarathne, D.N.N; Krishan, H.A.S; Wijesiri, M.R.M; Thelijjagoda, S; Jayawickrama, J. A. D. T.This research paper presents “MiMi”, a Sinhala Language voice assistive gamified solution that is designed to address stuttering in children aged between three and fourteen. Speech disorders occur when the regular flow of communication is disrupted. Stuttering, Lisps, Dysarthria, and Apraxia are some variations of speech impairments. Stuttering can be caused by a variety of factors including physical weaknesses, inherited diseases, Autism, and accidents. The risk of continuing to stutter into adulthood is highest in children between the ages of three to fourteen. It is recognized that stuttering therapy activities were less effective in managing stuttering after this age. Stuttering treatments comprise speech therapy with speech-language therapists, which requires in-person sessions that can be challenging and expensive in some circumstances. A parent’s financial ability, their busy schedules, the state of the economy in the nation, and the feasibility of physically seeing therapists and enduring treatments are all factors that might encourage or demotivate participation in therapy sessions. The development in technology and technical approaches have revolutionized the medical field and several studies have been conducted regarding communication disorders in recent years. The application can be used to practice a child’s needed speech therapy virtually and can also be used to aid speech therapy sessions done by speech therapists. The main aim of the system is to provide a customized, engaging, and innovative therapeutic strategy for children to manage stuttering.Publication Embargo Automated Spelling Checker And Grammatical Error Detection And Correction Model for Sinhala Language(IEEE, 2022-10-04) Goonawardena, M; Kulatunga, A; Wickramasinghe, R; Weerasekara, T; De Silva, H; Thelijjagoda, SSinhala is a native language spoken by the Sinhalese people, the largest ethnic group in Sri Lanka. It is a morphologically rich language, which is a derivation of Pali and Sanskrit. The Sinhala language creates a diglossia situation, as the language’s written form differs from its spoken form. With this difference, the written form requires more complex rules to be followed when in use. Manually proofreading the content of Sinhala material takes up much time and labor, and it can be a tedious task. Hence, a system is necessary which can be used by different industries such as journalism and even students. At present, there are a handful of systems and research that have automated Sinhala spelling analysis and grammar analysis. In addition, the existing systems are mainly focused on either spelling analysis or grammar analysis. However, the proposed system will cover both aspects and improve upon existing work by either optimizing or re-building the process to provide accurate outputs. The proposed system consists of a suffix list built for verbs and subjects, which helps the system stand out from the current proposed solutions. This research intends to implement a service for spell checking and grammar correctness of formal context in Sinhala. The research follows a rule-based approach with some components adopting a hybrid approach. As per the literature survey, many papers were analyzed, related to different aspects of the proposed system and complete systems. The proposed system would be able to overcome most barriers faced by previous papers whilst it takes a fresh take on providing a solution.Publication Embargo Dynamic stopword removal for Sinhala Language(IEEE, 2019-10-08) Jayaweera, A. A. V. A; Senanayake, Y. N; Haddela, P. SIn the modern era of information retrieval, text summarization, text analytics, extraction of redundant (noise) words that contain a little information with low or no semantic meaning must be filtered out. Such words are known as stopwords. There are more than 40 languages which have identified their language specific stopwords. Most researchers use various techniques to identify their language specific stopword lists. But most of them try to define a magical cut-off point to the list, which they identify without any proof. In this research, the focus is to prove that the cut-off point depends on the source data and the machine learning algorithm, which will be proved by using Newton's iteration method of root finding algorithm. To achieve this, the research focuses on creating a stopword list for Sinhala language using the term frequency-based method by processing more than 90000 Sinhala documents. This paper presents the results received and new datasets prepared for text preprocessing.Publication Embargo Enhanced Tokenizer for Sinhala Language(IEEE, 2019-10-08) Senanayake, S. Y; Kariyawasam, K. T. P. M; Haddela, P. STokenization process plays a prominent role in natural language processing (NLP) applications. It chops the content into the smallest meaningful units. However, there is a limited number of tokenization approaches for Sinhala language. Standard analyzer in apache software library and natural language toolkit (NLTK) are the main existing approaches to tokenize Sinhala language content. Since these are language independent, there are some limitations when it applies to Sinhala. Our proposed Sinhala tokenizer is mainly focusing on punctuation-based tokenization. It precisely tokenizes the content by identifying the use case of punctuation mark. In our research, we have proved that our punctuation-based tokenization approach outperforms the word tokenization in existing approaches.Publication Embargo A rule based stemmer for Sinhala language(IEEE, 2020-04-13) Kariyawasam, K. T. P. M; Wickramasinghe, S. Y; Haddela, P. SStemming, as its word implies it converts the original word into its root/base format which is called as stem. Stemming process plays a prominent role in natural language processing (NLP) because it makes applications more efficient and effective. Though stemming is such an important task, it is hard to find a stemming method for Sinhalese language which is official language of Sri Lanka. There are common language analyzers which cannot be use for stemming since they are highly language dependent. In this paper, we present a rule-based stemming method by using suffix and prefix rules in Sinhalese language.Publication Embargo Plagiarism Detection Tool for Sinhala Language with Internet Resources Using Natural Language Processing(IEEE, 2021-08-11) Rajamanthri, L; Thelijjagoda, SWith the digitalization of text through the World Wide Web, plagiarism turned into a crucial problem and a way to detect plagiarism became an essential component. Even though there are many plagiarism detection systems, applying in the world by considering other languages, for Sinhala it’s only a few, and it senses a vacuum in the domain. With the significant improvement of availability in Sinhala text on WWW, still, there is no system to detect plagiarism for these Sinhala documents by comparing resources on the internet. The purpose of this research is to address and overcome the above-mentioned gap while introducing a plagiarism detection system for the Sinhala language, by using internet resources. In the process to obtain the outcome, text pre-processing, Google searching and similarity comparison using Jaccard coefficient were the steps followed. As the final product, a Sinhala plagiarism detection tool was developed with 88% accuracy. The outcome of the work will be a support for the lectures, teachers, authors, students who are using Sinhala as their literal language.Publication Embargo Sinhala language decoder(IEEE, 2018-10-02) Vidanaralage, A. J; Illangakoon, A. U; Sumanaweera, S. Y; Pavithra, C; Thelijjagoda, SThe 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.