The MADAR Shared Task on Arabic Fine-Grained Dialect Identification

Houda Bouamor; Sabit Hassan; Nizar Habash

doi:10.18653/v1/W19-4622

The MADAR Shared Task on Arabic Fine-Grained Dialect Identification

Houda Bouamor, Sabit Hassan, Nizar Habash

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present the results and findings of the MADAR Shared Task on Arabic Fine-Grained Dialect Identification. This shared task was organized as part of The Fourth Arabic Natural Language Processing Workshop, collocated with ACL 2019. The shared task includes two subtasks: the MADAR Travel Domain Dialect Identification subtask (Subtask 1) and the MADAR Twitter User Dialect Identification subtask (Subtask 2). This shared task is the first to target a large set of dialect labels at the city and country levels. The data for the shared task was created or collected under the Multi-Arabic Dialect Applications and Resources (MADAR) project. A total of 21 teams from 15 countries participated in the shared task.

Original language	Undefined
Title of host publication	Proceedings of the Fourth Arabic Natural Language Processing Workshop
Place of Publication	Florence, Italy
Publisher	Association for Computational Linguistics (ACL)
Pages	199-207
Number of pages	9
DOIs	https://doi.org/10.18653/v1/W19-4622
State	Published - Aug 1 2019

Access to Document

10.18653/v1/W19-4622

https://www.aclweb.org/anthology/W19-4622

Cite this

@inproceedings{31de5e7d97244b70acd1be754b4139cd,

title = "The MADAR Shared Task on Arabic Fine-Grained Dialect Identification",

abstract = "In this paper, we present the results and findings of the MADAR Shared Task on Arabic Fine-Grained Dialect Identification. This shared task was organized as part of The Fourth Arabic Natural Language Processing Workshop, collocated with ACL 2019. The shared task includes two subtasks: the MADAR Travel Domain Dialect Identification subtask (Subtask 1) and the MADAR Twitter User Dialect Identification subtask (Subtask 2). This shared task is the first to target a large set of dialect labels at the city and country levels. The data for the shared task was created or collected under the Multi-Arabic Dialect Applications and Resources (MADAR) project. A total of 21 teams from 15 countries participated in the shared task.",

author = "Houda Bouamor and Sabit Hassan and Nizar Habash",

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doi = "10.18653/v1/W19-4622",

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N2 - In this paper, we present the results and findings of the MADAR Shared Task on Arabic Fine-Grained Dialect Identification. This shared task was organized as part of The Fourth Arabic Natural Language Processing Workshop, collocated with ACL 2019. The shared task includes two subtasks: the MADAR Travel Domain Dialect Identification subtask (Subtask 1) and the MADAR Twitter User Dialect Identification subtask (Subtask 2). This shared task is the first to target a large set of dialect labels at the city and country levels. The data for the shared task was created or collected under the Multi-Arabic Dialect Applications and Resources (MADAR) project. A total of 21 teams from 15 countries participated in the shared task.

AB - In this paper, we present the results and findings of the MADAR Shared Task on Arabic Fine-Grained Dialect Identification. This shared task was organized as part of The Fourth Arabic Natural Language Processing Workshop, collocated with ACL 2019. The shared task includes two subtasks: the MADAR Travel Domain Dialect Identification subtask (Subtask 1) and the MADAR Twitter User Dialect Identification subtask (Subtask 2). This shared task is the first to target a large set of dialect labels at the city and country levels. The data for the shared task was created or collected under the Multi-Arabic Dialect Applications and Resources (MADAR) project. A total of 21 teams from 15 countries participated in the shared task.

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