Yaregal AssabieMengistu Gebre2025-08-172025-08-172024-03https://etd.aau.edu.et/handle/123456789/6882A spell checker is an essential tool in Natural Language Processing (NLP). Its purpose is to identify and correct spelling errors in text, providing suggestions for correct spellings in a specific language. Spelling errors can be categorized into two types: non-word errors and real-word errors. Non-word errors are misspelled words that have no meaning in the particular language, while real-word errors involve words that exist in the language but are used incorrectly in terms of semantics and syntax. The research focused on non-word error detection as a strategic decision, given the complexity and limited resources available for the Gurage language, also known as Guragina. This language consists of over thirteen varieties and different orthographies, but there is a modern standard. Currently, there is no existing spell checker for any Guragina Language varieties or the standard. Addressing non-word errors first provides a solid foundation before tackling the more challenging task of real-word error detection and correction. This phased approach allows researchers to make meaningful progress on this under-resourced language, rather than attempting to solve the entire spell checking problem at once. The intention is to use the non-word spell checker as a starting point, then leverage that knowledge to progressively tackle real-word error handling. This work introduce a non-word spell error checker for the standard Guragina Language. The system detects and corrects errors using Ratcliff algorithms for identification and distance calculator techniques for correction. The prototype of the system was developed using Python. We evaluate the performance of the system using metrics such as accuracy of 98.27%, precession of 98.07%, recall of 97.75%, and F1 Score of 95.45%. Future work includes enhancing rule definitions by incorporating word classes, handling exceptions, adding supplementary spell checker functionalities, and expanding the system to encompass real-word errors.en-USSpell CheckerGurage LanguageMorphologyMorphological AnalysisLinguistic ResourcesRule-Based ApproachUnder-Resourced LanguagesThesis