Abstract

There are many studies about using lemmatization and spell-checker with spell-correction regarding English, Arabic, and Persian languages but only few studies found regarding low-resource languages such as Kurdish language and more specifically for Kurmanji dialect, which increased the need of creating such systems. Lemmatization is the process of determining a base or dictionary form (lemma) for a specific surface pattern, whereas spell-checkers and spell-correctors determine whether a word is correctly spelled also correct a range of spelling errors, respectively. This research aims to present a lemmatization and a word-level error correction system for Kurdish Kurmanji Dialect, which are the first tools for this dialect based on our knowledge. The proposed approach for lemmatization is built on morphological rules, and a hybrid approach that relies on the n-gram language model and the Jaccard Coefficient Similarity algorithm was applied to the spell-checker and spell-correction. The process results for lemmatization, as detailed in this article, rates of 97.7% and 99.3% accuracy for noun and verb lemmatization, correspondingly. Furthermore, for spell-checker and spell-correction, accordingly, accuracy rates of 100% and 90.77% are attained.

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