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AfriCLIRMatrix

AfriCLIRMatrix is a test collection for cross-lingual information retrieval research in 15 diverse African languages. This resource comprises English queries with query–document relevance judgments in 15 African languages automatically mined from Wikipedia...

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AfriCLIRMatrix: Enabling Cross-Lingual Information Retrieval for African Languages

Language diversity in NLP is critical in enabling the development of tools for a wide range of users.However, there are limited resources for building such tools for many languages, particularly those spoken in Africa.For search, most existing datasets feature few ...

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AfriSenti

AfriSenti is the largest sentiment analysis dataset for under-represented African languages, covering 110,000+ annotated tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oro...

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AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages

Africa is home to over 2000 languages from over six language families and has the highest linguistic diversity among all continents. This includes 75 languages with at least one million speakers each. Yet, there is little NLP research conducted on African languages...

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Arabic Dialect Identification in the Wild

We present QADI, an automatically collected dataset of tweets belonging to a wide range of country-level Arabic dialects -covering 18 different countries in the Middle East and North Africa region. Our method for building this dataset relies on applying multiple fi...

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BERT Fine-tuning For Arabic Text Summarization

Fine-tuning a pretrained BERT model is the state of the art method for extractive/abstractive text summarization, in this paper we showcase how this fine-tuning method can be applied to the Arabic language to both construct the first documented model for abstractiv...

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Can Character-based Language Models Improve Downstream Task Performances In Low-Resource And Noisy Language Scenarios?

Recent impressive improvements in NLP, largely based on the success of contextual neural language models, have been mostly demonstrated on at most a couple dozen high- resource languages. Building language mod- els and, more generally, NLP systems for non- standard...

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Goud.ma: a News Article Dataset for Summarization in Moroccan Darija

Moroccan Darija is a vernacular spoken by over 30 million people primarily in Morocco. Despite a high number of speakers, it remains a low-resource language. In this paper, we introduce Goud.ma: a dataset of over 158k news articles for automatic summarization in co...

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GOUD.MA: A NEWS ARTICLE DATASET FOR SUMMARIZATION IN MOROCCAN DARIJA

Goud dataset contains 158k articles and their headlines extracted from Goud.ma news website. The articles are written in the Arabic script. All headlines are in Moroccan Darija, while articles may be in Moroccan Darija, in Modern Standard Arabic, or a mix of both (...

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GOUD.MA: Summarization Models for Moroccan Darija

We train encoder-decoder baselines that are available on HuggingFace. We warm-start the model with pretrained BERT checkpoints and finetune it for the task of Text Summarization.

Identifying Sentiments in Algerian Code-switched User-generated Comments

We present in this paper our work on Algerian language, an under-resourced North African colloquial Arabic variety, for which we built a comparably large corpus of more than 36,000 code-switched user-generated comments annotated for sentiments. We opted for this da...

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Maghrebi Arabic

This chapter gives an overview of contact-induced changes in the Maghrebi dialect group in North Africa. It includes both a general summary of relevant research on the topic and a selection of case studies which exemplify contact-induced changes in the areas of pho...

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Moroccan Arabic

Morocco, even if the disputed Western Sahara is excluded, is rivaled only by Yemen in its variety of Arabic dialects. Latin/Romance sub- and ad-strata have played crucial roles in this, especially 1. when Arabized Berbers first encountered Romans; 2. during the Mus...

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NLLB-CLIP -- train performant multilingual image retrieval model on a budget

Today, the exponential rise of large models developed by academic and industrial institutions with the help of massive computing resources raises the question of whether someone without access to such resources can make a valuable scientific contribution. To explor...

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NLLB: No Language Left Behind

No Language Left Behind (NLLB) is a first-of-its-kind, AI breakthrough project that open-sources models capable of delivering high-quality translations directly between any pair of 200+ languages — including low-resource languages like Asturian, Luganda, Urdu and m...

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