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

Domain:

natural language processing

Record type:

paper
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 code-switched Moroccan Darija. We analyze the dataset and find that it requires a high level of abstractive reasoning. We fine-tune the Arabic-language BERT (AraBERT), and the language models for the Moroccan (DarijaBERT), and Algerian (DziriBERT) national vernaculars for summarization on Goud.ma. The results show that Goud.ma is a challenging summarization benchmark dataset. We release our dataset publicly in an effort to encourage the diversity of evaluation tasks to improve language modeling in Moroccan Darija.

Visit

openreview.net

Connected records

datasetmodel

Tasks

summarizationnatural language generation

Languages

Arabic, Moroccan Spoken

Tags

africanlp2

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GOUD.MA: A NEWS ARTICLE DATASET FOR SUMMARIZATION IN MOROCCAN DARIJAGOUD.MA: Summarization Models for Moroccan Darija

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 (

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.