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A Recipe for Arabic-English Neural Machine Translation [article]

Abdullah Alrajeh
2018 arXiv   pre-print
In this paper, we present a recipe for building a good Arabic-English neural machine translation.  ...  We also investigate the importance of special preprocessing of the Arabic script. The presented results are based on test sets from NIST MT 2005 and 2012.  ...  One of the investigated task is translation between Arabic and English but without special preprocessing for Arabic.  ... 
arXiv:1808.06116v1 fatcat:d4jzulum35ehbplg5jzvi3mr5q

Investigating the Effect of Preprocessing Arabic Text on Offensive Language and Hate Speech Detection

Fatemah Husain, Özlem Uzuner
2022 ACM Transactions on Asian and Low-Resource Language Information Processing  
This study aims to investigate the impact of preprocessing on Arabic offensive language classification.  ...  Transformers (BERT)-based models to analyze the impact of preprocessing.  ...  Our former study demonstrated the significant impact of intensive preprocessing on the performance of a Support Vector Machine (SVM) classifier.  ... 
doi:10.1145/3501398 dblp:journals/talip/HusainU22 fatcat:m5cili3tqrddtmpuga2qzcdube

Construction of Amharic-arabic Parallel Text Corpus for Neural Machine Translation

Ibrahim Gashaw, Shashirekha
2020 International Journal of Artificial Intelligence & Applications  
Therefore, a small parallel Quranic text corpus is constructed by modifying the existing monolingual Arabic text and its equivalent translation of Amharic language text corpora available on Tanzile.  ...  Experiments are carried out on Two Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) based Neural Machine Translation (NMT) using Attention-based Encoder-Decoder architecture which is adapted  ...  Preprocessing of both Amharic and Arabic scripts will have a great impact on the performance of the NMT system.  ... 
doi:10.5121/ijaia.2020.11107 fatcat:5udwbpcbvrah5imcxuzppwpts4

Morphology-aware Word-Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation

Ahmed Tawfik, Mahitab Emam, Khaled Essam, Robert Nabil, Hany Hassan
2019 Proceedings of the Fourth Arabic Natural Language Processing Workshop  
Parallel corpora available for building machine translation (MT) models for dialectal Arabic (DA) are rather limited.  ...  The scarcity of resources has prompted the use of Modern Standard Arabic (MSA) abundant resources to complement the limited dialectal resource. However, clitics often differ between MSA and DA.  ...  Within the NMT context, Huck et al. 2017 studied the impact of linguistically-aware word segmentation on the translation from English to German.  ... 
doi:10.18653/v1/w19-4602 dblp:conf/wanlp/TawfikEENH19 fatcat:hrnonaofrjdyfnumtndaejywte

Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015 [article]

Hassan Sajjad, Nadir Durrani, Francisco Guzman, Preslav Nakov, Ahmed Abdelali, Stephan Vogel, Wael Salloum, Ahmed El Kholy, Nizar Habash
2016 arXiv   pre-print
The paper describes the Egyptian Arabic-to-English statistical machine translation (SMT) system that the QCRI-Columbia-NYUAD (QCN) group submitted to the NIST OpenMT'2015 competition.  ...  The competition focused on informal dialectal Arabic, as used in SMS, chat, and speech.  ...  Introduction We describe the Egyptian Arabic-to-English statistical machine translation (SMT) system of the QCN team for the NIST OpenMT'2015 evaluation campaign.  ... 
arXiv:1606.05759v1 fatcat:crqxdntx6fctdd7my5vjkqj7ai

Arabic Sentiment Analysis: An Empirical Study of Machine Translation's Impact

Amira Barhoumi, Chafik Aloulou, Nathalie Camelin, Yannick Estève, Lamia Hadrich Belguith
2018 Conference on Language Processing and Knowledge Management  
In this paper, we translate Arabic dataset into English and study the impact of machine translation while considering a standard Arabic system as a baseline.  ...  To deal with Arabic sentiment analysis, machine translation of English resources or Arabic texts may be applied to built Arabic sentiment analysis systems.  ...  In this paper, we focus on the task of Arabic Sentiment Analysis (ASA) studying the impact of machine translation from Arabic to English on sentiment texts.  ... 
dblp:conf/lpkm/BarhoumiACEB18 fatcat:ray5iregwfacnhrpqmzui5isni

Evaluation of recent advances in recommender systems on Arabic content

Mehdi Srifi, Ahmed Oussous, Ayoub Ait Lahcen, Salma Mouline
2021 Journal of Big Data  
For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content.  ...  AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content.  ...  Acknowledgements The authors thank anonymous reviewers for their valuable comments and suggestions.  ... 
doi:10.1186/s40537-021-00420-2 fatcat:u554dtyp7jfk7gozfu5aadpfbe

Arabic Natural Language Processing and Machine Learning-Based Systems

Souad Larabi Marie-Sainte, Nada Alalyani, Sihaam Alotaibi, Sanaa Ghouzali, Ibrahim Abunadi
2019 IEEE Access  
On the other hand, the methodology of ANLP applications based on ML involves several distinct phases.  ...  Moreover, this survey discusses the characteristics and complexity of the Arabic language in addition to the importance and needs of ANLP.  ...  ACKNOWLEDGMENT The authors would like to thank the Deanship of Scientific Research and RSSU at King Saud University for their technical support.  ... 
doi:10.1109/access.2018.2890076 fatcat:d5xxdsuq6bg4lbmivnq7d27iom

Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions [article]

Marcin Junczys-Dowmunt and Tomasz Dwojak and Hieu Hoang
2016 arXiv   pre-print
In this paper we provide the largest published comparison of translation quality for phrase-based SMT and neural machine translation across 30 translation directions.  ...  In the second part of the paper we investigate aspects of translation speed, introducing AmuNMT, our efficient neural machine translation decoder.  ...  We also see large improvements for translations out of and into Arabic. No special preprocessing has been applied for Arabic.  ... 
arXiv:1610.01108v3 fatcat:qxvp2bmxwzhgpgwyvofbfitm2e

Tw-StAR at SemEval-2018 Task 1: Preprocessing Impact on Multi-label Emotion Classification

Hala Mulki, Chedi Bechikh Ali, Hatem Haddad, Ismail Babaoglu
2018 Proceedings of The 12th International Workshop on Semantic Evaluation  
This has been later emphasized by the official results as our system ranked 3 rd for both Arabic and Spanish datasets and 14 th for the English dataset.  ...  We investigated using single and combinations of several preprocessing tasks to further improve the performance.  ...  Moreover, other ML methods could be examined with BR and deep neural models. Table 1 : 1 Statistics of the used datasets.  ... 
doi:10.18653/v1/s18-1024 dblp:conf/semeval/MulkiAHB18 fatcat:yajfglv6mnctrfj45szmwemroa

A Multilingual Offensive Language Detection Method based on Transfer Learning from Transformer Fine-tuning Model

Fatima-zahra EL-ALAMI, Said OUATIK EL ALAOUI, Noureddine EN NAHNAHI
2021 Journal of King Saud University: Computer and Information Sciences  
The experimental findings show that the translation-based method in conjunction with Arabic BERT (AraBERT) achieves over 93% and 91% in terms of F1-score and accuracy, respectively.  ...  The proposed system consists of several stages: (1) Preprocessing, (2) Text representation using BERT models, and (3) Classification into two categories: Offensive and nonoffensive.  ...  We also project to explore some disambiguation methods in order to tackle the ambiguity problem, when we follow the translation-based strategy, and enhance the performances.  ... 
doi:10.1016/j.jksuci.2021.07.013 fatcat:2cqm4k7rkzfuzfynodwtamolpu

How Much Does Tokenization Affect Neural Machine Translation? [article]

Miguel Domingo and Mercedes Garcıa-Martınez and Alexandre Helle and Francisco Casacuberta and Manuel Herranz
2019 arXiv   pre-print
In order to assess the impact of the tokenization in the quality of the final translation on NMT, we experimented on five tokenizers over ten language pairs.  ...  Neural Machine Translation (NMT) requires a limited-size vocabulary for computational cost and enough examples to estimate word embeddings.  ...  Some previous works include studying the effect of word-level preprocessing for Arabic on Statistical Machine Translation (SMT).  ... 
arXiv:1812.08621v4 fatcat:xzzhgly5rjat3bqirrbvm6ogma

Urdu-English Machine Transliteration using Neural Networks [article]

Usman Mohy ud Din
2020 arXiv   pre-print
This approach is tested on three models of statistical machine translation (SMT) which include phrasebased, hierarchical phrase-based and factor based models and two models of neural machine translation  ...  Among different translation techniques, neural network currently leading the domain with its capabilities of providing a single large neural network with attention mechanism, sequence-to-sequence and long-short  ...  The details of different models of statistical machine translation and neural machine translation adapted in this experiment are given below.  ... 
arXiv:2001.05296v1 fatcat:5zgacud2dfg5jiuzock7x5l4tq

RUTUT: Roman Urdu to Urdu Translator Based on Character Substitution Rules and Unicode Mapping

Mobeen Shahroz, Muhammad Faheem Mushtaq, Arif Mehmood, Saleem Ullah, Gyu Sang Choi
2020 IEEE Access  
Convolutional Neural Network (CNN) based sequence to sequence character mapping techniques, phrased based statistical models of machine learning and conventional techniques based on NLP techniques are  ...  Then the neural machine translation model translates the Roman Urdu to Urdu script. BLEU [50] evaluation metric is used that is 48.6 on the test.  ...  Computer machines are all working on the functionality of Unicode based linguistic. Then those converted Urdu characters create words and sentences. Figure 16  ... 
doi:10.1109/access.2020.3031393 fatcat:5obqf4z4y5dyxedbuwiyoaddvy

Arabic Machine Translation: A Survey with Challenges and Future Directions

Jezia Zakraoui, Moutaz Saleh, Somaya Al-Maadeed, Jihad Mohamad AlJa'am
2021 IEEE Access  
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.  ...  The statements made herein are solely the responsibility of the authors.  ...  ACKNOWLEDGMENT This work was made possible by NPRP grant #10-0205-170346 from the Qatar National Research Fund (a member of Qatar Foundation).  ... 
doi:10.1109/access.2021.3132488 fatcat:bxa4wlfi5ffyhlhbxkcxsgp5aq
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