151 citations · 538 across the 29 of their papers we have counts for
35 papers
Perception, performance, and detectability of conversational artificial intelligence across 32 university courses
Hazem Ibrahim, Fengyuan Liu, Rohail Asim +36
The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the incr…
Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation
Bashar Alhafni, Go Inoue, Christian Khairallah +1
Grammatical error correction (GEC) is a well-explored problem in English with many existing models and datasets. However, research on GEC in morphologically rich languages has been…
Maknuune: A Large Open Palestinian Arabic Lexicon
Shahd Dibas, Christian Khairallah, Nizar Habash +4
We present Maknuune, a large open lexicon for the Palestinian Arabic dialect. Maknuune has over 36K entries from 17K lemmas, and 3.7K roots. All entries include diacritized Arabic…
Camelira: An Arabic Multi-Dialect Morphological Disambiguator
Ossama Obeid, Go Inoue, Nizar Habash
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 Levan…
Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition
Injy Hamed, Amir Hussein, Oumnia Chellah +5
Code-switching poses a number of challenges and opportunities for multilingual automatic speech recognition. In this paper, we focus on the question of robust and fair evaluation m…
ArzEn-ST: A Three-way Speech Translation Corpus for Code-Switched Egyptian Arabic - English
Injy Hamed, Nizar Habash, Slim Abdennadher +1
We present our work on collecting ArzEn-ST, a code-switched Egyptian Arabic - English Speech Translation Corpus. This corpus is an extension of the ArzEn speech corpus, which was c…
The Shared Task on Gender Rewriting
Bashar Alhafni, Nizar Habash, Houda Bouamor +11
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. T…
NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +2
We describe findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state of the art Arabic NLP, including on Arabic dialects. I…
Arabic Word-level Readability Visualization for Assisted Text Simplification
Reem Hazim, Hind Saddiki, Bashar Alhafni +2
This demo paper presents a Google Docs add-on for automatic Arabic word-level readability visualization. The add-on includes a lemmatization component that is connected to a five-l…
The User-Aware Arabic Gender Rewriter
Bashar Alhafni, Ossama Obeid, Nizar Habash
We introduce the User-Aware Arabic Gender Rewriter, a user-centric web-based system for Arabic gender rewriting in contexts involving two users. The system takes either Arabic or E…
Exploring Segmentation Approaches for Neural Machine Translation of Code-Switched Egyptian Arabic-English Text
Marwa Gaser, Manuel Mager, Injy Hamed +3
Data sparsity is one of the main challenges posed by code-switching (CS), which is further exacerbated in the case of morphologically rich languages. For the task of machine transl…
User-Centric Gender Rewriting
Bashar Alhafni, Nizar Habash, Houda Bouamor
In this paper, we define the task of gender rewriting in contexts involving two users (I and/or You) - first and second grammatical persons with independent grammatical gender pref…
Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentation
Injy Hamed, Nizar Habash, Slim Abdennadher +1
Data sparsity is a main problem hindering the development of code-switching (CS) NLP systems. In this paper, we investigate data augmentation techniques for synthesizing dialectal…
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization
Moussa Kamal Eddine, Nadi Tomeh, Nizar Habash +2
Like most natural language understanding and generation tasks, state-of-the-art models for summarization are transformer-based sequence-to-sequence architectures that are pretraine…
The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses
Bashar Alhafni, Nizar Habash, Houda Bouamor
Gender bias in natural language processing (NLP) applications, particularly machine translation, has been receiving increasing attention. Much of the research on this issue has foc…
Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects
Go Inoue, Salam Khalifa, Nizar Habash
We present state-of-the-art results on morphosyntactic tagging across different varieties of Arabic using fine-tuned pre-trained transformer language models. Our models consistentl…
Automatic Error Type Annotation for Arabic
Riadh Belkebir, Nizar Habash
We present ARETA, an automatic error type annotation system for Modern Standard Arabic. We design ARETA to address Arabic's morphological richness and orthographic ambiguity. We ba…
NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany +2
We present the findings and results of the Second Nuanced Arabic Dialect Identification Shared Task (NADI 2021). This Shared Task includes four subtasks: country-level Modern Stand…
The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models
Go Inoue, Bashar Alhafni, Nurpeiis Baimukan +2
In this paper, we explore the effects of language variants, data sizes, and fine-tuning task types in Arabic pre-trained language models. To do so, we build three pre-trained langu…
NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task
Muhammad Abdul-Mageed, Chiyu Zhang, Houda Bouamor +1
We present the results and findings of the First Nuanced Arabic Dialect Identification Shared Task (NADI). This Shared Task includes two subtasks: country-level dialect identificat…
A Panoramic Survey of Natural Language Processing in the Arab World
Kareem Darwish, Nizar Habash, Mourad Abbas +9
The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design. This distinguishes natural langu…
The Paradigm Discovery Problem
Alexander Erdmann, Micha Elsner, Shijie Wu +2
This work treats the paradigm discovery problem (PDP), the task of learning an inflectional morphological system from unannotated sentences. We formalize the PDP and develop evalua…
Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling
Nasser Zalmout, Nizar Habash
Morphological tagging is challenging for morphologically rich languages due to the large target space and the need for more training data to minimize model sparsity. Dialectal vari…
Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging
Nasser Zalmout, Nizar Habash
Semitic languages can be highly ambiguous, having several interpretations of the same surface forms, and morphologically rich, having many morphemes that realize several morphologi…