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Since Arabic is an agglutinating language by nature, this treatment becomes a crucial preprocessing step for many Natural Language Processing (NLP) applications such as morphological analysis, parsing, machine translation, information extraction, and so on. In this article, we investigate word tokenization task with a rewriting process to rewrite the orthography of the stem. For this task, we are using Tunisian Arabic (TA) text. To the best of the researchers\u2019 knowledge, this is the first study that uses TA for word tokenization. Therefore, we start by collecting and preparing various TA corpora from different sources. Then, we present a comparison of three character-based tokenizers based on Conditional Random Fields (CRF), Support Vector Machines (SVM) and Deep Neural Networks (DNN). The best proposed model using CRF achieved an F-measure result of 88.9%.<\/jats:p>","DOI":"10.1145\/3599234","type":"journal-article","created":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T12:17:35Z","timestamp":1684930655000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Tokenization of Tunisian Arabic: A Comparison between Three Machine Learning Models"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3140-3171","authenticated-orcid":false,"given":"Asma","family":"Mekki","sequence":"first","affiliation":[{"name":"ANLP Research Group, MIRACL Lab., University of Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2065-7873","authenticated-orcid":false,"given":"In\u00e8s","family":"Zribi","sequence":"additional","affiliation":[{"name":"ANLP Research Group, MIRACL Lab., ISIMa, University of Monastir, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1864-2602","authenticated-orcid":false,"given":"Mariem","family":"Ellouze","sequence":"additional","affiliation":[{"name":"ANLP Research Group, MIRACL Lab., University of Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4868-657X","authenticated-orcid":false,"given":"Lamia Hadrich","family":"Belguith","sequence":"additional","affiliation":[{"name":"ANLP Research Group, MIRACL Lab., University of Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,7,20]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3003"},{"key":"e_1_3_2_3_2","first-page":"1","volume-title":"Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013","author":"Abdul-Mageed Muhammad","year":"2013","unstructured":"Muhammad Abdul-Mageed, Mona Diab, and Sandra K\u00fcbler. 2013. 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