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This paper reports on the participation of Techlimed in the Second Shared Task on Automatic Arabic Error Correction organized by the Arabic Natural Language Processing Workshop. This year's competition includes two tracks, and, in addition to errors produced by native speakers (L1), also includes correction of texts written by learners of Arabic as a foreign language (L2). Techlimed participated in the L1 track. For our participation in the L1 evaluation task, we developed two systems. The first one is based on the spellchecker Hunspell with specific dictionaries. The second one is a hybrid system based on rules, morphology analysis and statistical machine translation. Our results on the test set show that the hybrid system outperforms the lexicon driven approach with a precision of 71.2%, a recall of 64.94% and an F-measure of 67.93%.

TECHLIMED$@$QALB-Shared Task 2015: a hybrid Arabic Error Correction System