Building Dialectal Arabic Corpora

Hani Abdalla Muftah Elgabou; Dimitar Lubomirov Kazakov

Building Dialectal Arabic Corpora

Hani Abdalla Muftah Elgabou, Dimitar Lubomirov Kazakov

Computer Science

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

Abstract

The aim of this research is to identify local Arabic dialects in texts from social media (Twitter) and link them to specific geographic areas. Dialect identification is studied as a subset of the task of language identification. The proposed method is based on unsupervised learning using simultaneously lexical and geographic distance. While this study focusses on Libyan dialects, the approach is general, and could produce resources to support human translators and interpreters when dealing with vernaculars rather than standard Arabic.

Original language	English
Title of host publication	The First Workshop on Human-Informed Translation and Interpreting Technology (HiT-IT)
Pages	52-57
Number of pages	6
Publication status	Published - 7 Sep 2017
Event	First Workshop on Human-Informed Translation and Interpreting Technology - Varna, Bulgaria Duration: 7 Sep 2017 → 7 Sep 2017 http://rgcl.wlv.ac.uk/hit-it/

Conference

Conference	First Workshop on Human-Informed Translation and Interpreting Technology
Abbreviated title	HiT-IT
Country/Territory	Bulgaria
City	Varna
Period	7/09/17 → 7/09/17
Internet address	http://rgcl.wlv.ac.uk/hit-it/

Access to Document

http://rgcl.wlv.ac.uk/wp-content/uploads/2017/09/06/book.pdfLicence: Unspecified

Cite this

@inproceedings{9f69c25732514661b0ce1d78e4691d3a,

title = "Building Dialectal Arabic Corpora",

abstract = "The aim of this research is to identify local Arabic dialects in texts from social media (Twitter) and link them to specific geographic areas. Dialect identification is studied as a subset of the task of language identification. The proposed method is based on unsupervised learning using simultaneously lexical and geographic distance. While this study focusses on Libyan dialects, the approach is general, and could produce resources to support human translators and interpreters when dealing with vernaculars rather than standard Arabic.",

author = "Elgabou, {Hani Abdalla Muftah} and Kazakov, {Dimitar Lubomirov}",

year = "2017",

month = sep,

day = "7",

language = "English",

pages = "52--57",

booktitle = "The First Workshop on Human-Informed Translation and Interpreting Technology (HiT-IT)",

note = "First Workshop on Human-Informed Translation and Interpreting Technology, HiT-IT ; Conference date: 07-09-2017 Through 07-09-2017",

url = "http://rgcl.wlv.ac.uk/hit-it/",

}

TY - GEN

T1 - Building Dialectal Arabic Corpora

AU - Elgabou, Hani Abdalla Muftah

AU - Kazakov, Dimitar Lubomirov

PY - 2017/9/7

Y1 - 2017/9/7

N2 - The aim of this research is to identify local Arabic dialects in texts from social media (Twitter) and link them to specific geographic areas. Dialect identification is studied as a subset of the task of language identification. The proposed method is based on unsupervised learning using simultaneously lexical and geographic distance. While this study focusses on Libyan dialects, the approach is general, and could produce resources to support human translators and interpreters when dealing with vernaculars rather than standard Arabic.

AB - The aim of this research is to identify local Arabic dialects in texts from social media (Twitter) and link them to specific geographic areas. Dialect identification is studied as a subset of the task of language identification. The proposed method is based on unsupervised learning using simultaneously lexical and geographic distance. While this study focusses on Libyan dialects, the approach is general, and could produce resources to support human translators and interpreters when dealing with vernaculars rather than standard Arabic.

M3 - Conference contribution

SP - 52

EP - 57

BT - The First Workshop on Human-Informed Translation and Interpreting Technology (HiT-IT)

T2 - First Workshop on Human-Informed Translation and Interpreting Technology

Y2 - 7 September 2017 through 7 September 2017

ER -