ADIDA: Automatic dialect identification for Arabic

Ossama Obeid, Mohammad Salameh, Houda Bouamor, Nizar Habash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This demo paper describes ADIDA, a webbased system for automatic dialect identification for Arabic text. The system distinguishes among the dialects of 25 Arab cities (from Rabat to Muscat) in addition to Modern Standard Arabic. The results are presented with either a point map or a heat map visualizing the automatic identification probabilities over a geographical map of the Arab World.

Original languageEnglish (US)
Title of host publicationNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies - Proceedings of the Demonstrations Session
PublisherAssociation for Computational Linguistics (ACL)
Pages6-11
Number of pages6
ISBN (Electronic)9781950737161
StatePublished - 2019
Event2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States
Duration: Jun 2 2019Jun 7 2019

Publication series

NameNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Demonstrations Session

Conference

Conference2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
CountryUnited States
CityMinneapolis
Period6/2/196/7/19

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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