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Social media user-generated text is actually the main resource for many NLPtasks. This text however, does not follow the standard rules of writing.Moreover, the use of dialect such as Moroccan Arabic in written communicationsincreases further NLP tasks complexity. A dialect is a verbal language thatdoes not have a standard orthography, which leads users to improvise spellingwhile writing. Thus, for the same word we can find multiple forms oftransliterations. Subsequently, it is mandatory to normalize these differenttransliterations to one canonical word form. To reach this goal, we haveexploited the powerfulness of word embedding models generated with a corpus ofYouTube comments. Besides, using a Moroccan Arabic dialect dictionary thatprovides the canonical forms, we have built a normalization dictionary that werefer to as MANorm. We have conducted several experiments to demonstrate theefficiency of MANorm, which have shown its usefulness in dialect normalization.

MANorm: A Normalization Dictionary for Moroccan Arabic Dialect Written in Latin Script