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Found 17 papers, 2 papers with code
Arabic Diacritics in the Wild: Exploiting Opportunities for Improved Diacritization
The widespread absence of diacritical marks in Arabic text poses a significant challenge for Arabic natural language processing (NLP).
Camelira: An Arabic Multi-Dialect Morphological Disambiguator
We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine.
The Shared Task on Gender Rewriting
In this paper, we present the results and findings of the Shared Task on Gender Rewriting, which was organized as part of the Seventh Arabic Natural Language Processing Workshop.
The User-Aware Arabic Gender Rewriter
We introduce the User-Aware Arabic Gender Rewriter, a user-centric web-based system for Arabic gender rewriting in contexts involving two users.
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
ADIDA: Automatic Dialect Identification for Arabic
This demo paper describes ADIDA, a web-based system for automatic dialect identification for Arabic text.
An Arabic Morphological Analyzer and Generator with Copious Features
We introduce CALIMA-Star, a very rich Arabic morphological analyzer and generator that provides functional and form-based morphological features as well as built-in tokenization, phonological representation, lexical rationality and much more.
MADARi: A Web Interface for Joint Arabic Morphological Annotation and Spelling Correction
In this paper, we introduce MADARi, a joint morphological annotation and spelling correction system for texts in Standard and Dialectal Arabic.
Guidelines and Framework for a Large Scale Arabic Diacritized Corpus
This paper presents the annotation guidelines developed as part of an effort to create a large scale manually diacritized corpus for various Arabic text genres.
Building an Arabic Machine Translation Post-Edited Corpus: Guidelines and Annotation
We present our guidelines and annotation procedure to create a human corrected machine translated post-edited corpus for the Modern Standard Arabic.
Large Scale Arabic Error Annotation: Guidelines and Framework
Finally, we present the annotation tool that was developed as part of this project, the annotation pipeline, and the quality of the resulting annotations.
