QC-GO submission for madar shared task: Arabic fine-grained dialect identification

  • Younes Samih
  • , Hamdy Mubarak
  • , Ahmed Abdelali
  • , Mohammed Attia
  • , Mohamed Eldesouki
  • , Kareem Darwish

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper describes the QC-GO team submission to the MADAR Shared Task Subtask 1 (travel domain dialect identification) and Subtask 2 (Twitter user location identification). In our participation in both subtasks, we explored a number of approaches and system combinations to obtain the best performance for both tasks. These include deep neural nets and heuristics. Since individual approaches suffer from various shortcomings, the combination of different approaches was able to fill some of these gaps. Our system achieves F1-Scores of 66.1% and 67.0% on the development sets for Subtasks 1 and 2 respectively.

Original languageEnglish
Title of host publicationACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages290-294
Number of pages5
ISBN (Electronic)9781950737321
Publication statusPublished - 2019
Event4th Arabic Natural Language Processing Workshop, WANLP 2019, held at ACL 2019 - Florence, Italy
Duration: 1 Aug 2019 → …

Publication series

NameACL 2019 - 4th Arabic Natural Language Processing Workshop, WANLP 2019 - Proceedings of the Workshop

Conference

Conference4th Arabic Natural Language Processing Workshop, WANLP 2019, held at ACL 2019
Country/TerritoryItaly
CityFlorence
Period1/08/19 → …

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