MORPHOLOGY BASED SPELLING CHECKER FOR GEEZ LANGUAGE

dc.contributor.authorFIKADE CHANE FELEKE
dc.date.accessioned2026-01-26T06:17:25Z
dc.date.issued2023-03-06
dc.description.abstractGeez is one of the ancient languages. It belongs to Semitic language family. Many ancient literature and books have written in Geez. Currently, Geez course are offered in various colleges, universities and in some primary schools. However, still developed NLP applications are insufficient for this language. In order to write error free Geez text in less time, spelling checker application is a critical NLP application. Spelling checker is a tool used to detect spelling error in a block of text and gives closer suggestions to the error words. A previous attempt has made to develop a spelling checker for Geez language. This attempt was focus only homophone alphabet interchangeably error. In this study, we proposed morphology based (dictionary lookup and morphological analyzer) approach to Geez language spelling checker. The system have three main compenents.These are text preprocessing, error detection, and error correction. To achieve the objective of this study the researcher builds one main dictionaries that contains Geez language lexicon and morphological feature. The researcher built 6115 unique Geez lexicon and 955 rules had defined. We adopt the Hunspell dictionary and affix file format to design a lexicon (i.e. the knowledge base component) and hashing algorithm for searching. Hunspell is an open source spelling checker tool. It has designed especially for languages that have complex morphology. Finally, the researcher has developed a prototype of a system to test the functionality and performance of the Geez language spelling checker. The accuracy of error detection expressed in terms of precision and recall. In addition, the accuracy of suggestion expressed in terms of suggestion adequacy. Therefore, we got the result of lexical recall 91.9%, error recall 83.7%, lexical precision 97.2%, error precision 62.2% and correct suggestions provided by GLSC 87.5%. The overall performance of the system is 90.05%. We conclude that increase the size of the dictionary and develop well organized rule will increase the overall performance of the Geez language spelling checker.
dc.identifier.urihttps://etd.hu.edu.et/handle/123456789/213
dc.language.isoen
dc.publisherHawassa University
dc.subjectError Detection
dc.subjectError Correction
dc.subjectSpell Checker
dc.subjectMorphology
dc.subjectNon Word Error
dc.subjectReal Word Error
dc.subjectGeez language
dc.subjectdictionary lookup
dc.titleMORPHOLOGY BASED SPELLING CHECKER FOR GEEZ LANGUAGE
dc.typeThesis

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