Search Results for author: Ahmed Abdelali

Found 52 papers, 4 papers with code

Improving Arabic Text Categorization Using Transformer Training Diversification

1 code implementation COLING (WANLP) 2020 Shammur Absar Chowdhury, Ahmed Abdelali, Kareem Darwish, Jung Soon-Gyo, Joni Salminen, Bernard J. Jansen

Automatic categorization of short texts, such as news headlines and social media posts, has many applications ranging from content analysis to recommendation systems.

Recommendation Systems Text Categorization

Adult Content Detection on Arabic Twitter: Analysis and Experiments

no code implementations EACL (WANLP) 2021 Hamdy Mubarak, Sabit Hassan, Ahmed Abdelali

With Twitter being one of the most popular social media platforms in the Arab region, it is not surprising to find accounts that post adult content in Arabic tweets; despite the fact that these platforms dissuade users from such content.

QADI: Arabic Dialect Identification in the Wild

no code implementations EACL (WANLP) 2021 Ahmed Abdelali, Hamdy Mubarak, Younes Samih, Sabit Hassan, Kareem Darwish

For extrinsic evaluation, we are able to build effective country level dialect identification on tweets with a macro-averaged F1-score of 60. 6% across 18 classes.

Dialect Identification

NatiQ: An End-to-end Text-to-Speech System for Arabic

no code implementations15 Jun 2022 Ahmed Abdelali, Nadir Durrani, Cenk Demiroglu, Fahim Dalvi, Hamdy Mubarak, Kareem Darwish

We concatenated Tacotron1 with the WaveRNN vocoder, Tacotron2 with the WaveGlow vocoder and ESPnet transformer with the parallel wavegan vocoder to synthesize waveforms from the spectrograms.

Code-Switching Text Augmentation for Multilingual Speech Processing

no code implementations7 Jan 2022 Amir Hussein, Shammur Absar Chowdhury, Ahmed Abdelali, Najim Dehak, Ahmed Ali

The pervasiveness of intra-utterance Code-switching (CS) in spoken content has enforced ASR systems to handle mixed input.

Text Augmentation Translation

Automatic Expansion and Retargeting of Arabic Offensive Language Training

no code implementations18 Nov 2021 Hamdy Mubarak, Ahmed Abdelali, Kareem Darwish, Younes Samih

Rampant use of offensive language on social media led to recent efforts on automatic identification of such language.

Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASR

no code implementations31 May 2021 Shammur Absar Chowdhury, Amir Hussein, Ahmed Abdelali, Ahmed Ali

We evaluate the system performance handling: (i) monolingual (Ar, En and Fr); (ii) multi-dialectal (Modern Standard Arabic, along with dialectal variation such as Egyptian and Moroccan); (iii) code-switching -- cross-lingual (Ar-En/Fr) and dialectal (MSA-Egyptian dialect) test cases, and compare with current state-of-the-art systems.

Automatic Speech Recognition speech-recognition

ASAD: Arabic Social media Analytics and unDerstanding

no code implementations EACL 2021 Sabit Hassan, Hamdy Mubarak, Ahmed Abdelali, Kareem Darwish

This system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets.

Pre-Training BERT on Arabic Tweets: Practical Considerations

no code implementations21 Feb 2021 Ahmed Abdelali, Sabit Hassan, Hamdy Mubarak, Kareem Darwish, Younes Samih

The experiments highlight the centrality of data diversity and the efficacy of linguistically aware segmentation.

BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets

no code implementations COLING (WANLP) 2020 Fouzi Harrag, Maria Debbah, Kareem Darwish, Ahmed Abdelali

To the best of our knowledge, this work is the first study where ARABERT and GPT2 were combined to detect and classify the Arabic auto-generated texts.

Face Swapping Transfer Learning +1

ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social Media

no code implementations SEMEVAL 2020 Sabit Hassan, Younes Samih, Hamdy Mubarak, Ahmed Abdelali

This paper describes the systems submitted by the Arabic Language Technology group (ALT) at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media.

Language Identification

Arabic Curriculum Analysis

no code implementations COLING 2020 Hamdy Mubarak, Shimaa Amer, Ahmed Abdelali, Kareem Darwish

Developing a platform that analyzes the content of curricula can help identify their shortcomings and whether they are tailored to specific desired outcomes.

Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms

1 code implementation15 Jul 2020 Firoj Alam, Fahim Dalvi, Shaden Shaar, Nadir Durrani, Hamdy Mubarak, Alex Nikolov, Giovanni Da San Martino, Ahmed Abdelali, Hassan Sajjad, Kareem Darwish, Preslav Nakov

With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories.


Arabic Dialect Identification in the Wild

no code implementations13 May 2020 Ahmed Abdelali, Hamdy Mubarak, Younes Samih, Sabit Hassan, Kareem Darwish

We present QADI, an automatically collected dataset of tweets belonging to a wide range of country-level Arabic dialects -covering 18 different countries in the Middle East and North Africa region.

Dialect Identification

Arabic Offensive Language on Twitter: Analysis and Experiments

no code implementations EACL (WANLP) 2021 Hamdy Mubarak, Ammar Rashed, Kareem Darwish, Younes Samih, Ahmed Abdelali

Detecting offensive language on Twitter has many applications ranging from detecting/predicting bullying to measuring polarization.

Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model

no code implementations4 Feb 2020 Kareem Darwish, Ahmed Abdelali, Hamdy Mubarak, Mohamed Eldesouki

Our model surpasses all previous state-of-the-art systems with a CW error rate (CWER) of 2. 86\% and a CE error rate (CEER) of 3. 7% for Modern Standard Arabic (MSA) and CWER of 2. 2% and CEER of 2. 5% for Classical Arabic (CA).

Feature Engineering

A System for Diacritizing Four Varieties of Arabic

no code implementations IJCNLP 2019 Hamdy Mubarak, Ahmed Abdelali, Kareem Darwish, Mohamed Eldesouki, Younes Samih, Hassan Sajjad

Short vowels, aka diacritics, are more often omitted when writing different varieties of Arabic including Modern Standard Arabic (MSA), Classical Arabic (CA), and Dialectal Arabic (DA).

Feature Engineering

QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification

no code implementations WS 2019 Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Mohammed Attia, Mohamed Eldesouki, Kareem Darwish

This paper describes the QC-GO team submission to the MADAR Shared Task Subtask 1 (travel domain dialect identification) and Subtask 2 (Twitter user location identification).

Dialect Identification

ArbEngVec : Arabic-English Cross-Lingual Word Embedding Model

no code implementations WS 2019 Raki Lachraf, El Moatez Billah Nagoudi, Youcef Ayachi, Ahmed Abdelali, Didier Schwab

Word Embeddings (WE) are getting increasingly popular and widely applied in many Natural Language Processing (NLP) applications due to their effectiveness in capturing semantic properties of words; Machine Translation (MT), Information Retrieval (IR) and Information Extraction (IE) are among such areas.

Information Retrieval Machine Translation +5

POS Tagging for Improving Code-Switching Identification in Arabic

no code implementations WS 2019 Mohammed Attia, Younes Samih, Ali Elkahky, Hamdy Mubarak, Ahmed Abdelali, Kareem Darwish

When speakers code-switch between their native language and a second language or language variant, they follow a syntactic pattern where words and phrases from the embedded language are inserted into the matrix language.


Diacritization of Maghrebi Arabic Sub-Dialects

no code implementations15 Oct 2018 Ahmed Abdelali, Mohammed Attia, Younes Samih, Kareem Darwish, Hamdy Mubarak

Diacritization process attempt to restore the short vowels in Arabic written text; which typically are omitted.

Interpreting Strategies Annotation in the WAW Corpus

no code implementations RANLP 2017 Irina Temnikova, Ahmed Abdelali, Samy Hedaya, Stephan Vogel, Aishah Al Daher

In this article we run an automatic analysis of a corpus of parallel speeches and their human interpretations, and provide the results of manually annotating the human interpreting strategies in a sample of the corpus.

Machine Translation Speech-to-Text Translation +1

Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM

2 code implementations19 Aug 2017 Mohamed Eldesouki, Younes Samih, Ahmed Abdelali, Mohammed Attia, Hamdy Mubarak, Kareem Darwish, Kallmeyer Laura

Arabic word segmentation is essential for a variety of NLP applications such as machine translation and information retrieval.

 Ranked #1 on Sentiment Analysis on DynaSent (using extra training data)

Domain Adaptation Information Retrieval +3

Learning from Relatives: Unified Dialectal Arabic Segmentation

no code implementations CONLL 2017 Younes Samih, Mohamed Eldesouki, Mohammed Attia, Kareem Darwish, Ahmed Abdelali, Hamdy Mubarak, Laura Kallmeyer

Arabic dialects do not just share a common koin{\'e}, but there are shared pan-dialectal linguistic phenomena that allow computational models for dialects to learn from each other.

Dialect Identification Information Retrieval +1

Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet

no code implementations WS 2017 Kareem Darwish, Hamdy Mubarak, Ahmed Abdelali, Mohamed Eldesouki

However, we show that augmenting bi-LSTM sequence labeling with some of the features that we used for the SVM-Rank based tagger yields to further improvements.

Feature Engineering Named Entity Recognition +3

A Neural Architecture for Dialectal Arabic Segmentation

no code implementations WS 2017 Younes Samih, Mohammed Attia, Mohamed Eldesouki, Ahmed Abdelali, Hamdy Mubarak, Laura Kallmeyer, Kareem Darwish

The automated processing of Arabic Dialects is challenging due to the lack of spelling standards and to the scarcity of annotated data and resources in general.

Machine Translation Morphological Analysis +1

Arabic Diacritization: Stats, Rules, and Hacks

no code implementations WS 2017 Kareem Darwish, Hamdy Mubarak, Ahmed Abdelali

In this paper, we present a new and fast state-of-the-art Arabic diacritizer that guesses the diacritics of words and then their case endings.

Part-Of-Speech Tagging Transliteration +1

Arabic to English Person Name Transliteration using Twitter

no code implementations LREC 2016 Hamdy Mubarak, Ahmed Abdelali

We present a novel approach for mining data from Twitter for the purpose of building transliteration resources and systems.

Translation Transliteration

The AMARA Corpus: Building Parallel Language Resources for the Educational Domain

no code implementations LREC 2014 Ahmed Abdelali, Francisco Guzman, Hassan Sajjad, Stephan Vogel

This paper presents the AMARA corpus of on-line educational content: a new parallel corpus of educational video subtitles, multilingually aligned for 20 languages, i. e. 20 monolingual corpora and 190 parallel corpora.

Machine Translation Translation

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