Language identification (" LI") is the problem of determining the natural language that a
document or part thereof is written in. Automatic LI has been extensively researched for over …

This paper introduces a supervised approach for performing sentence level dialect
identification between Modern Standard Arabic and Egyptian Dialectal Arabic. We use token …

Word-level language detection is necessary for analyzing code-switched text, where
multiple languages could be mixed within a sentence. Existing models are restricted to code …

Social media users have the proclivity to write majority of the data for under resourced
languages in code-mixed format. Code-mixing is defined as mixing of two or more …

This paper presents a multi-dialect, multi-genre, human annotated corpus of dialectal Arabic.
We collected utterances in five Arabic dialects: Levantine, Gulf, Egyptian, Iraqi and …

This paper describes the HHU-UH-G system submitted to the EMNLP 2016 Second
Workshop on Computational Approaches to Code Switching. Our system ranked first place …

This paper describes the process of creating a novel resource, a parallel Arabizi-Arabic
script corpus of SMS/Chat data. The language used in social media expresses many …

We describe the system built by the National Research Council Canada for the”
Discriminating between similar languages”(DSL) shared task. Our system uses various …

Arabic on social media has all the properties of any language on social media that make it
tough for natural language processing, plus some specific problems. These include …

In this paper, we present the latest version of our system for identifying linguistic code
switching in Arabic text. The system relies on Language Models and a tool for morphological …