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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/530

Title: Spell and Grammar Checking Tool for Sinhalese
Other Titles: අකුරු ස ෝදුව - සියබ සුබ ක් කරනු රිසිසයනි
Authors: Abeyrathne, Lahiru
Premachandra, Rumesh
Warsha, Apsaari
Edirisinghe, Surangi
Keywords: Natural language processing
Machine learning
Data analysis
Accuracy
Automate suggestions
Issue Date: 14-Jun-2018
Series/Report no.: ;17-116
Abstract: Sinhala language has its own writing system, which is which an offspring of the Brahmi script Maldives is and Dhivehi languages. Sinhalese alphabet contains many numbers of letters to produce Sinhala words, basically it divided into vowels and consonants. In addition, Sinhalese contain many number of spell and grammar rules in writing. The main intention of this “සියබස සුබසක් කරනු රිසියයනි” (Spell and grammar checking tool for Sinhalese) research is to provide a web based system to check the correctness of the spelling and grammar of Sinhala language. Purpose of this research is to ensure the effective use of Sinhala language through facilitating means of learning correct grammar and to protect the language for the benefit of the next generation. Proposed outcome will provide provisions for the end users to manually type or copy paste a word, word phrase or even a paragraph and to check the correctness of the spelling and grammar in real time. It will also provide suggestions for the users to manipulate a sentence. The solution will be using various high-end techniques in Natural Language Processing, Machine Learning and Data analytics in order to enhance the computer interaction. Existing systems can only giving facility to check spelling. Any Sinhala grammar checking tool or a system not existing at present. This introducing system can go beyond that existing spell checking system with much more accuracy. Introduce system can give grammar checking facility with the automate suggestions for correct sentences to make this product valuable.
URI: http://hdl.handle.net/123456789/530
Appears in Collections:SLIIT Student Research -2017

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