Tamil Grammarly - A Typing Assistant for Tamil Language using Natural Language Processing

• Published in: 2023 3rd International Conference on Advanced Research in Computing (ICARC) pp. 154 - 159
• Main Authors: Mahadevan, Praveen, Srihari, Parameswaran, Seyon, Krishnathasan, Vasavan, Parthipan, Panchendrarajan, Rrubaa
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23-02-2023
• Subjects: Asia; Focusing; Grammar; Grammar Checking; Natural language processing; Next word Prediction; Real-time systems; Spell Checking; Synonym Suggestion; Transformers
• DOI: 10.1109/ICARC57651.2023.10145744

Tamil is one of the ancient and most convoluted languages in the world. Although it is being the official language of many Asian countries, even native speakers tend to find difficulties in writing Tamil due to its morphologically rich nature. While there are various studies focusing on automatically identifying and correcting a specific typing error, very limited effort has been made to develop a comprehensive solution to assist the native and non-native writers of Tamil. In this paper, we propose a typing assistant tool Tamil Grammarly using Natural Language Processing (NLP) techniques. Specifically, the tool aims to aid the user to fix grammatical errors and spelling errors and recommend the next words and synonyms of the current word in real-time while typing. The NLP-based typing assistant functions of Tamil Grammarly were developed using a transformer-based model, LSTM model, and Word2Vec model. Extensive evaluation performed shows that our tool can assist the users in real-time with an accuracy of 73% - 93% within 0.4 to 5.3 seconds.