Hierarchical Aggregation of Dialectal Data for Arabic Dialect Identification

Nurpeiis Baimukan, Houda Bouamor, Nizar Habash

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

Abstract

Arabic is a collection of dialectal variants that are historically related but significantly different. These differences can be seen across regions, countries, and even cities in the same countries. Previous work on Arabic Dialect identification has focused mainly on specific dialect levels (region, country, province, or city) using level-specific resources; and different efforts used different schemas and labels. In this paper, we present the first effort aiming at defining a standard unified three-level hierarchical schema (region-country-city) for dialectal Arabic classification. We map 29 different data sets to this unified schema, and use the common mapping to facilitate aggregating these data sets. We test the value of such aggregation by building language models and using them in dialect identification. We make our label mapping code and aggregated language models publicly available.

Original languageEnglish (US)
Title of host publication2022 Language Resources and Evaluation Conference, LREC 2022
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Pages4586-4596
Number of pages11
ISBN (Electronic)9791095546726
StatePublished - 2022
Event13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
Duration: Jun 20 2022Jun 25 2022

Publication series

Name2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Country/TerritoryFrance
CityMarseille
Period6/20/226/25/22

Keywords

  • Arabic Dialects
  • Dialect Identification
  • Language Models

ASJC Scopus subject areas

  • Language and Linguistics
  • Library and Information Sciences
  • Linguistics and Language
  • Education

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