MADOran: A morphologically annotated dataset of Oran

This paper introduces a new morphologically annotated dataset for the Orani Arabic dialect (ORN), comprising 30,919 words gathered from diverse genres, including written language (41 %) which cover topics such as culture, history, politics, recipes, social issues, tourism, and traditions, as well as spoken language (59 %) spanning stories, songs, TV scenes, proverbs, relationships and daily conversation such as college life, family, and relationships. Each word is manually annotated with a fine-grained tagset that provides part-of-speech, root, pattern, and English and French translations of the glosses. The morphological annotation was performed using the Dialectal Word Annotation Tool for Arabic (DIWAN) and it followed guidelines established for The Dynamic Arabella Corpus (Arabella), with adaptations to fit the dialectal context. MADOran, the Morphologically Annotated Dataset of Oran, presents a valuable resource for natural language processing applications that are focused on Arabic dialect processing, including dialect identification, machine translation, text generation, and speech recognition. It enables the training of language models for capturing the unique morphological and syntactic characteristics of ORN. Moreover, the dataset supports any linguistic research where features of ORN and Modern Standard Arabic (MSA) are compared and whenever the features unique to each variety are discussed. It also aids in developing dialect-specific lexicographic resources and in facilitating Arabic language learning. The annotated dataset adheres to scientific data stewardship principles of findability, accessibility, interoperability, and reusability, which qualify MADOran for use across domains.