English

DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings

Artificial Intelligence 2021-03-16 v2

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 embedding. 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. Our benchmark, evaluation code, and new word embedding models will be publicly available.

Keywords

Cite

@article{arxiv.2011.10970,
  title  = {DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings},
  author = {Muhammad Abdul-Mageed and Shady Elbassuoni and Jad Doughman and AbdelRahim Elmadany and El Moatez Billah Nagoudi and Yorgo Zoughby and Ahmad Shaher and Iskander Gaba and Ahmed Helal and Mohammed El-Razzaz},
  journal= {arXiv preprint arXiv:2011.10970},
  year   = {2021}
}

Comments

WANLP2021

R2 v1 2026-06-23T20:25:23.514Z