Natural Language Processing for Arabic dialects has grown widely these last years. Indeed,
several works were proposed dealing with all aspects of Natural Language Processing …

Arabic dialects also called colloquial Arabic or vernaculars are spoken varieties of Standard
Arabic. These dialects have mixed form with many variations due to the influence of ancient …

Formality transfer seeks to adjust text formality without altering its core meaning, which
carries substantial implications across diverse domains like machine translation, dialogue …

Deep Learning is one of the most promising technologies compared to other methods in the
context of machine translation. It has been proven to achieve impressive results on large …

This study is the first work on a transductive transfer learning approach for low-resource
neural machine translation applied to the Algerian Arabic dialect. The transductive approach …

This paper aims to present a machine translation system capable of translating Tunisian
Dialect (TD) text to Modern Standard Arabic (MSA) using a rule-based approach. Having …

In this paper, we present the first work on unsupervised dialectal Neural Machine
Translation (NMT), where the source dialect is not represented in the parallel training …

Abstract While Modern Standard Arabic (MSA) has many resources, Arabic Dialects, the
primarily spoken local varieties of Arabic, are quite impoverished in this regard. In this …

Diglossia is one of the main characteristics of Arabic language. In Arab countries, there are
three forms of Arabic that co-exist: Classical Arabic (CA) which is mainly used in the Quran …

Tokenization represents the way of segmenting a piece of text into smaller units called
tokens. Since Arabic is an agglutinating language by nature, this treatment becomes a …