Evaluation of Arabic language readability

Readability plays an important role in the process of choosing materials adapted to readers' levels. Indeed, the task of automatically measuring the readability of a text frequently faces challenges such as lack of data and resources.In this thesis, we have produced a set of models for automatic readability prediction. These models are dedicated to readers of Arabic as a first language (L1) and as a foreign language (L2). The development of these models involves three main stages. The first step consists in collecting a reference corpus annotated according to levels of difficulty. The second step consists in converting the texts into feature vectors. The final stage in the development of a predictive readability model is a classification phase.In the final part of this thesis, we have exploited all the resources and models we have developed for an initial investigation into the field of text simplification.

Autorentext

Nassiri Naoual has been a professor at the École supérieure de technologie-Dakhla-Maroc since 2022. She was awarded a national PhD in Computer Science in 2021. Her research focuses on natural language processing and computational linguistics (readability evaluation, machine learning, and automatic simplification).