{"title":"MICHAEL: Mining Character-level Patterns for Arabic Dialect Identification (MADAR Challenge)","authors":"Dhaou Ghoul, Gaël Lejeune","doi":"10.18653/v1/W19-4627","DOIUrl":null,"url":null,"abstract":"We present MICHAEL, a simple lightweight method for automatic Arabic Dialect Identification on the MADAR travel domain Dialect Identification (DID). MICHAEL uses simple character-level features in order to perform a pre-processing free classification. More precisely, Character N-grams extracted from the original sentences are used to train a Multinomial Naive Bayes classifier. This system achieved an official score (accuracy) of 53.25% with 1<=N<=3 but showed a much better result with character 4-grams (62.17% accuracy).","PeriodicalId":268163,"journal":{"name":"WANLP@ACL 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WANLP@ACL 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W19-4627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
We present MICHAEL, a simple lightweight method for automatic Arabic Dialect Identification on the MADAR travel domain Dialect Identification (DID). MICHAEL uses simple character-level features in order to perform a pre-processing free classification. More precisely, Character N-grams extracted from the original sentences are used to train a Multinomial Naive Bayes classifier. This system achieved an official score (accuracy) of 53.25% with 1<=N<=3 but showed a much better result with character 4-grams (62.17% accuracy).
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