Classification of closely related sub-dialects of Arabic using support-vector machines

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

Abstract

Colloquial dialects of Arabic can be roughly categorized into five groups based on relatedness and geographic location (Egyptian, North African/Maghrebi, Gulf, Iraqi, and Levantine), but given that all dialects utilize much of the same writing system and share overlapping features and vocabulary, dialect identification and text classification is no trivial task. Furthermore, text classification by dialect is often performed at a coarse-grained level into these five groups or a subset thereof, and there is little work on sub-dialectal classification. The current study utilizes an n-gram based SVM to classify on a fine-grained sub-dialectal level, and compares it to methods used in dialect classification such as vocabulary pruning of shared items across dialects. A test case of the dialect Levantine is presented here, and results of 65% accuracy on a four-way classification experiment to sub-dialects of Levantine (Jordanian, Lebanese, Palestinian and Syrian) are presented and discussed. This paper also examines the possibility of leveraging existing mixed-dialectal resources to determine their sub-dialectal makeup by automatic classification.

Original languageEnglish (US)
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages3671-3674
Number of pages4
ISBN (Electronic)9791095546009
StatePublished - 2019
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Publication series

NameLREC 2018 - 11th International Conference on Language Resources and Evaluation

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
CountryJapan
CityMiyazaki
Period5/7/185/12/18

Keywords

  • Language identification
  • Text classification
  • Validation of language resources

ASJC Scopus subject areas

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

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  • Cite this

    Wray, S. (2019). Classification of closely related sub-dialects of Arabic using support-vector machines. In H. Isahara, B. Maegaard, S. Piperidis, C. Cieri, T. Declerck, K. Hasida, H. Mazo, K. Choukri, S. Goggi, J. Mariani, A. Moreno, N. Calzolari, J. Odijk, & T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 3671-3674). (LREC 2018 - 11th International Conference on Language Resources and Evaluation). European Language Resources Association (ELRA).