https://jjcit.org/paper/178 10.5455/jjcit.71-1655499240 Asma Mekki,Inès Zribi,Mariem Ellouze,Lamia Hadrich Belguith* Orthographic normalization,Tunisian Arabic,COTA Orthography system,CODA-TA 5 5515 1604 17-Jun.-2022 7-Sep.-2022 and 18-Oct.-2022 10-Nov.-2022 In written text, orthographic noise is a common concern for NLP, especially when operating social-network comments and raw documents. This is mainly due to its orthographic conventions and morphological ambiguity. We propose to automatically normalize the social-media dialect corpora by following CODA-TA, the conventional Orthography for TA. The existing system developed for TA «COTA Orthography 1.0» is not able to handle all forms of TA. Therefore, we propose to extend its rules and lexicons to address the peculiarities of social media dialect. In certain words, the COTA Orthography 1.0 system provides the user with several correction possibilities. Therefore, in the new version, we incorporated a trigram language model to automatically select the right correction. Our results show that the system can reduce transcription errors by 95.72%.