Nizar Habash · page 4
Papers
- First Result on Arabic Neural Machine Translation (2016 · 40 citations)
This short 2016 paper reports the first fully neural machine translation results for Arabic, in both directions (Ar→En and En→Ar). - Domain and Dialect Adaptation for Machine Translation into Egyptian Arabic (2014 · 40 citations)
The paper tackles translation from English into Egyptian Arabic, a dialect with almost no parallel data, no standard spelling, and poor support from Modern Standard Arabic (MSA) tools. - Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation (2023 · 38 citations)
The paper addresses grammatical error correction (GEC) and grammatical error detection (GED) in Arabic (MSA). - Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling (2019 · 37 citations)
The authors tag fourteen Arabic morphological features (POS, aspect, case, gender, and others) with one Bi-LSTM whose hidden layers are shared across features, instead of one model per feature. - Botta: An Arabic Dialect Chatbot (2016 · 36 citations)
Arabic is poorly served by conversational agents, and its spoken dialects even more so. Dialects have no standard spelling, heavy inflection and ambiguity, and their own conversational formulas. The authors build BOTTA, which they describe as the earliest chatbot able to hold a conversation in a dialect of Arabic. It… - Morphologically Annotated Corpora for Seven Arabic Dialects: Taizi, Sanaani, Najdi, Jordanian, Syrian, Iraqi and Moroccan (2019 · 34 citations)
The paper releases seven small manually annotated corpora of Arabic dialects (Taizi and Sanaani Yemeni, Najdi, Jordanian, Syrian Damascene, Iraqi Baghdadi, Moroccan Rabati), together over 200,000 words, each about 20,000 to 35,000 words. - The Columbia System in the QALB-2014 Shared Task on Arabic Error Correction (2014 · 34 citations)
This paper presents Columbia University's entry in QALB-2014, the first shared task on automatic error correction for Modern Standard Arabic. - OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model (2017 · 33 citations)
The paper tackles sentiment analysis of Arabic tweets within SemEval-2017 Task 4. Rich morphology, dialect variation, misspellings and Twitter-specific tokens make this task harder than in English. The OMAM team built four systems: - Arabic Corpora for Credibility Analysis (2016 · 33 citations)
The paper addresses a resource gap: credibility classifiers for social media need human-labelled training data, and before this work no public Arabic corpus of blogs or tweets had credibility annotations. - Generation-Heavy Hybrid Machine Translation (2002 · 32 citations)
The paper proposes a way to translate between structurally divergent languages when only the target language is rich in resources. - A Spelling Correction Corpus for Multiple Arabic Dialects (2020 · 31 citations)
Arabic dialects are widely written online but have no official spelling, so a single word can be spelled in many ways. - Annotating Targets of Opinions in Arabic using Crowdsourcing (2015 · 31 citations)
The paper addresses the lack of fine-grained opinion resources for Arabic. No public dataset marked what an opinion is about, and earlier fine-grained corpora in other languages relied on slow, costly expert annotators. The authors replace a single hard judgement with two simple crowdsourced steps on Amazon… - The SAMER Arabic Text Simplification Corpus (2024 · 30 citations)
Arabic, a morphologically rich language, has had no publicly released, manually built parallel corpus for text simplification. - A Parallel Corpus for Evaluating Machine Translation between Arabic and European Languages (2017 · 30 citations)
Most Arabic machine translation resources pair Arabic with English, and only a handful pair it with other languages. - CatVar: A Database of Categorial Variations for English (2003 · 30 citations)
CatVar is a database of categorial variations of English lexemes: a noun, a verb and an adjective that share one root, such as "destroy", "destruction" and "destructive". - Arabic Word-level Readability Visualization for Assisted Text Simplification (2022 · 29 citations)
Most readability tools score whole documents or sentences, so a human simplifier still has to find the specific words that need rewriting. - User-Centric Gender Rewriting (2022 · 29 citations)
The paper addresses how to tailor Arabic text to who is speaking and who is being addressed. In Arabic, words that refer to "I" or "you" often carry grammatical gender. A system that returns only one output therefore tends to assume a gender, usually masculine. The authors define gender rewriting : given a sentence… - Feature Optimization for Predicting Readability of Arabic L1 and L2 (2018 · 29 citations)
The paper addresses automatic readability assessment for Arabic, a morphologically rich language with relatively few resources. - A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment (2025 · 28 citations)
Arabic readability research has lacked a large, carefully balanced, finely graded dataset. The authors address this with BAREC (Balanced Arabic Readability Evaluation Corpus). It contains 69,441 sentence-level segments, totalling over a million words, drawn from many genres, topics and audiences. Each segment was… - ADIDA: Automatic Dialect Identification for Arabic (2019 · 28 citations)
Written Arabic dialects are hard to tell apart automatically. They share one script and much vocabulary, and writers often mix dialect with Modern Standard Arabic (MSA). Most earlier dialect identification worked only at the level of regions or countries. This demo paper presents ADIDA, a public web tool built on the… - Creating Resources for Dialectal Arabic from a Single Annotation: A Case Study on Egyptian and Levantine (2016 · 28 citations)
Arabic dialects lack standard spelling, linguistic documentation and annotated data, yet they are increasingly written on social media. - Camelira: An Arabic Multi-Dialect Morphological Disambiguator (2022 · 27 citations)
Camelira is a public web interface that disambiguates Arabic sentences in four varieties: MSA, Egyptian, Gulf and Levantine. - A Large-Scale Leveled Readability Lexicon for Standard Arabic (2020 · 27 citations)
The paper tackles the lack of graded vocabulary resources for Modern Standard Arabic (MSA) for native-speaker reading, as part of the SAMER project (Simplification of Arabic Masterpieces for Extensive Reading). - Strategies for Arabic Readability Modeling (2024 · 26 citations)
The paper tackles automatic readability assessment for Modern Standard Arabic, which is hard because of rich morphology, orthographic ambiguity, and few resources. - The FIGNEWS Shared Task on News Media Narratives (2024 · 26 citations)
FIGNEWS was a shared task at Arabic-NLP 2024, held alongside ACL 2024. Its goal was less about building classifiers and more about learning how to write annotation guidelines for subjective, politically charged judgments. The case study was multilingual news coverage of the opening months of the Israel War on Gaza.…
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