With the widespread adoption of natural language processing (NLP) systems through chatbots, writing assistance, and translation... Under-represented languages are still far from having such achievements. This was due to the fact that large amount of data is needed to build such systems, which is not accessible for all languages. Therefore, the challenge has now become: how can we leverage the new NLP achievements to low-resource languages?

Abdellah will discuss how to use machine learning to build NLP Systems for low-resource languages, he will present this for the case of the Arabic language and its varieties. These approaches show to achieve high performance for low-resource languages using Zero-Labeled data.