@inproceedings{abdul-mageed-etal-2021-dialex,
title = "{D}ia{L}ex: A Benchmark for Evaluating Multidialectal {A}rabic Word Embeddings",
author = "Abdul-Mageed, Muhammad and
Elbassuoni, Shady and
Doughman, Jad and
Elmadany, AbdelRahim and
Nagoudi, El Moatez Billah and
Zoughby, Yorgo and
Shaher, Ahmad and
Gaba, Iskander and
Helal, Ahmed and
El-Razzaz, Mohammed",
editor = "Habash, Nizar and
Bouamor, Houda and
Hajj, Hazem and
Magdy, Walid and
Zaghouani, Wajdi and
Bougares, Fethi and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Touileb, Samia",
booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
month = apr,
year = "2021",
address = "Kyiv, Ukraine (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wanlp-1.2/",
pages = "11--20",
abstract = "Word embeddings are a core component of modern natural language processing systems, making the ability to thoroughly evaluate them a vital task. We describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word embeddings. DiaLex covers five important Arabic dialects: Algerian, Egyptian, Lebanese, Syrian, and Tunisian. Across these dialects, DiaLex provides a testbank for six syntactic and semantic relations, namely male to female, singular to dual, singular to plural, antonym, comparative, and genitive to past tense. DiaLex thus consists of a collection of word pairs representing each of the six relations in each of the five dialects. To demonstrate the utility of DiaLex, we use it to evaluate a set of existing and new Arabic word embeddings that we developed. Beyond evaluation of word embeddings, DiaLex supports efforts to integrate dialects into the Arabic language curriculum. It can be easily translated into Modern Standard Arabic and English, which can be useful for evaluating word translation. Our benchmark, evaluation code, and new word embedding models will be publicly available."
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%0 Conference Proceedings
%T DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings
%A Abdul-Mageed, Muhammad
%A Elbassuoni, Shady
%A Doughman, Jad
%A Elmadany, AbdelRahim
%A Nagoudi, El Moatez Billah
%A Zoughby, Yorgo
%A Shaher, Ahmad
%A Gaba, Iskander
%A Helal, Ahmed
%A El-Razzaz, Mohammed
%Y Habash, Nizar
%Y Bouamor, Houda
%Y Hajj, Hazem
%Y Magdy, Walid
%Y Zaghouani, Wajdi
%Y Bougares, Fethi
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Touileb, Samia
%S Proceedings of the Sixth Arabic Natural Language Processing Workshop
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv, Ukraine (Virtual)
%F abdul-mageed-etal-2021-dialex
%X Word embeddings are a core component of modern natural language processing systems, making the ability to thoroughly evaluate them a vital task. We describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word embeddings. DiaLex covers five important Arabic dialects: Algerian, Egyptian, Lebanese, Syrian, and Tunisian. Across these dialects, DiaLex provides a testbank for six syntactic and semantic relations, namely male to female, singular to dual, singular to plural, antonym, comparative, and genitive to past tense. DiaLex thus consists of a collection of word pairs representing each of the six relations in each of the five dialects. To demonstrate the utility of DiaLex, we use it to evaluate a set of existing and new Arabic word embeddings that we developed. Beyond evaluation of word embeddings, DiaLex supports efforts to integrate dialects into the Arabic language curriculum. It can be easily translated into Modern Standard Arabic and English, which can be useful for evaluating word translation. Our benchmark, evaluation code, and new word embedding models will be publicly available.
%U https://aclanthology.org/2021.wanlp-1.2/
%P 11-20
Markdown (Informal)
[DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings](https://aclanthology.org/2021.wanlp-1.2/) (Abdul-Mageed et al., WANLP 2021)
ACL
- Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Yorgo Zoughby, Ahmad Shaher, Iskander Gaba, Ahmed Helal, and Mohammed El-Razzaz. 2021. DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings. In Proceedings of the Sixth Arabic Natural Language Processing Workshop, pages 11–20, Kyiv, Ukraine (Virtual). Association for Computational Linguistics.