The morphological analysis is an important task for the Tunisian dialect processing because the dialect does not respect any standard and it is different for modern standard Arabic. In order to propose a method allowing the morphological analysis, we study many Tunisian dialect texts to identify different forms of written words. The proposed method is based on a self-constructed dictionary extracted from a corpus and a set of morphological local grammars implemented in the NooJ linguistic platform. Indeed, the morphological grammars are transformed into finite transducers while using NooJ’s new technologies. To test and evaluate the designed analyzer, we applied it on a Tunisian test corpus containing over 18,000 words. The obtained results are ambitious.
CITATION STYLE
Torjmen, R., & Haddar, K. (2018). Morphological aanalyzer for the tunisian dialect. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11107 LNAI, pp. 180–187). Springer Verlag. https://doi.org/10.1007/978-3-030-00794-2_19
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