Language model-based spell-checker for Sri Lankan names and addresses

Abstract

Names are used abundantly in various applications, but traditional spell-checkers are not adapted to correcting errors in names. In this research, we suggest a spell-checker for Sri Lankan names and addresses. The main challenge in building a spell checker for names is the inability to create a comprehensive dictionary. Our spell-checker overcomes this challenge by utilizing a language model for evaluating the validity of names and a non-Dictionary suggestion generator. The resulting spell-checker boasts performance of up to 96% suggestion adequacy. This spellchecker can be used in applications directly, and the components built can be repurposed for other named entity-related research.