no code implementations • COLING (WANLP) 2020 • Abdellah El Mekki, Ahmed Alami, Hamza Alami, Ahmed Khoumsi, Ismail Berrada
Around the Arab world, different Arabic dialects are spoken by more than 300M persons, and are increasingly popular in social media texts.
no code implementations • EACL (WANLP) 2021 • Abdellah El Mekki, Abdelkader El Mahdaouy, Kabil Essefar, Nabil El Mamoun, Ismail Berrada, Ahmed Khoumsi
Dialect and standard language identification are crucial tasks for many Arabic natural language processing applications.
1 code implementation • 28 Oct 2023 • Abdellah El Mekki, Muhammad Abdul-Mageed, ElMoatez Billah Nagoudi, Ismail Berrada, Ahmed Khoumsi
We also demonstrate the effectiveness of ProMap in re-ranking results from other BLI methods such as with aligned static word embeddings.
1 code implementation • SemEval (NAACL) 2022 • Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Abderrahman Skiredj, Ismail Berrada
Our system\footnote{The source code of our system is available at \url{https://github. com/AbdelkaderMH/iSarcasmEval}} consists of three deep learning-based models leveraging two existing pre-trained language models for Arabic and English.
no code implementations • 16 Jun 2022 • Abdelkader El Mahdaouy, Abdellah El Mekki, Ahmed Oumar, Hajar Mousannif, Ismail Berrada
The prevalence of toxic content on social media platforms, such as hate speech, offensive language, and misogyny, presents serious challenges to our interconnected society.
no code implementations • SemEval (NAACL) 2022 • Abdellah El Mekki, Abdelkader El Mahdaouy, Mohammed Akallouch, Ismail Berrada, Ahmed Khoumsi
This is due to the complexity and ambiguity of named entities that appear in various contexts such as short input sentences, emerging entities, and complex entities.
no code implementations • SEMEVAL 2021 • Kabil Essefar, Abdellah El Mekki, Abdelkader El Mahdaouy, Nabil El Mamoun, Ismail Berrada
Humor detection has become a topic of interest for several research teams, especially those involved in socio-psychological studies, with the aim to detect the humor and the temper of a targeted population (e. g. a community, a city, a country, the employees of a given company).
no code implementations • SEMEVAL 2021 • Nabil El Mamoun, Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Ismail Berrada
The proposed system consists of a deep learning model, based on pre-trained transformer encoder, for word and Multi-Word Expression (MWE) complexity prediction.
no code implementations • EACL (WANLP) 2021 • Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Nabil El Mamoun, Ismail Berrada, Ahmed Khoumsi
The prominence of figurative language devices, such as sarcasm and irony, poses serious challenges for Arabic Sentiment Analysis (SA).
no code implementations • 23 Jun 2021 • Abdellah El Mekki, Abdelkader El Mahdaouy, Kabil Essefar, Nabil El Mamoun, Ismail Berrada, Ahmed Khoumsi
Dialect and standard language identification are crucial tasks for many Arabic natural language processing applications.
1 code implementation • NAACL 2021 • Abdellah El Mekki, Abdelkader El Mahdaouy, Ismail Berrada, Ahmed Khoumsi
In this paper, we propose a new unsupervised domain adaptation method for Arabic cross-domain and cross-dialect sentiment analysis from Contextualized Word Embedding.
1 code implementation • 7 Feb 2021 • ElMehdi Boujou, Hamza Chataoui, Abdellah El Mekki, Saad Benjelloun, Ikram Chairi, Ismail Berrada
This includes applications for the Arabic language and its national dialects.