Moroccan Dialect -Darija- Open Dataset
This provides a standard resource for researchers and students interested in the Moroccan dialect, but it is incremental as it focuses on data collection rather than novel methods.
The authors tackled the lack of resources for the Moroccan dialect (Darija) by creating DODa, an open-source dataset with over 10,000 entries for English translation and NLP tasks, and demonstrated its use in image classification with ImageNet labels translated to Darija.
Darija Open Dataset (DODa) is an open-source project for the Moroccan dialect. With more than 10,000 entries DODa is arguably the largest open-source collaborative project for Darija-English translation built for Natural Language Processing purposes. In fact, besides semantic categorization, DODa also adopts a syntactic one, presents words under different spellings, offers verb-to-noun and masculine-to-feminine correspondences, contains the conjugation of hundreds of verbs in different tenses, and many other subsets to help researchers better understand and study Moroccan dialect. This data paper presents a description of DODa, its features, how it was collected, as well as a first application in Image Classification using ImageNet labels translated to Darija. This collaborative project is hosted on GitHub platform under MIT's Open-Source license and aims to be a standard resource for researchers, students, and anyone who is interested in Moroccan Dialect