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First Result on Arabic Neural Machine Translation [article]

Amjad Almahairi, Kyunghyun Cho, Nizar Habash, Aaron Courville
2016 arXiv   pre-print
We notice however that much of research on neural machine translation has focused on European languages despite its language agnostic nature.  ...  In this paper, we apply neural machine translation to the task of Arabic translation (Ar<->En) and compare it against a standard phrase-based translation system.  ...  In this paper, our aim is therefore to present the first result on the Arabic translation using neural machine translation.  ... 
arXiv:1606.02680v1 fatcat:z4obc77ghjbj3gdr35nnrmicbe

Large-Scale Machine Translation between Arabic and Hebrew: Available Corpora and Initial Results [article]

Yonatan Belinkov, James Glass
2016 arXiv   pre-print
In this work, we compare standard phrase-based and neural systems on Arabic-Hebrew translation.  ...  Machine translation between Arabic and Hebrew has so far been limited by a lack of parallel corpora, despite the political and cultural importance of this language pair.  ...  Acknowledgments The authors would like to thank Mauro Cettolo for useful suggestions with regards to the Arabic-Hebrew TED talks corpus, Pierre Lison and Jörg Tiedemann for help with getting access to  ... 
arXiv:1609.07701v1 fatcat:6mpzlyysk5furf53cqwaq7uccq

A Neural Machine Translation Model for Arabic Dialects That Utilizes Multitask Learning (MTL)

Laith H. Baniata, Seyoung Park, Seong-Bae Park
2018 Computational Intelligence and Neuroscience  
In this research article, we study the problem of employing a neural machine translation model to translate Arabic dialects to Modern Standard Arabic.  ...  The proposed solution of the neural machine translation model is prompted by the recurrent neural network-based encoder-decoder neural machine translation model that has been proposed recently, which generalizes  ...  Results and Discussion Neural machine translation experiments were presented by using the multitask learning approach on different translation tasks: machine translation from Modern Standard Arabic (MSA  ... 
doi:10.1155/2018/7534712 fatcat:n5s5ukeouvcxla374c2v5q3t7e

ATLASLang NMT: Arabic Text Language into Arabic Sign Language Neural Machine Translation

Mourad Brour, Abderrahim Benabbou
2019 Journal of King Saud University: Computer and Information Sciences  
ATLASLang is a machine translation system from Arabic text language into Arabic sign language (ArSL).  ...  In the last few years, a neural machine translation has achieved notable results, and several wellknown companies including Google (Wu et al., 2016) and Systran (Crego et al., 2016) have starting to exploit  ...  Almahairi gave the first results of an implementation of the neural network on Arabic language (Almahairi et al., 2016) ; this system translates a text in Arabic to a text in English and vice versa-it  ... 
doi:10.1016/j.jksuci.2019.07.006 fatcat:bg6r7tbjgrcqhnfa6ww3lyxwpi

Phrase Based and Neural Network Translation for Text Transliteration from Arabic to Indonesia

Alvian Burhanuddin, Ahmad Latif Qosim, Rizqi Amaliya
2022 MATICS  
Abstract- Transliteration is one solution to overcome the inability to read and write Arabic in Indonesia. However, this transliteration has many different versions in reality.  ...  The many differences in transliteration versions make it difficult for people to understand and pronounce the Arabic sentence.  ...  Statistical machine translation and neural machine translation produce 73% and 75% accuracy, respectively, on internal data. Meanwhile, on external data, it was found that the accuracy was only 45%.  ... 
doi:10.18860/mat.v14i1.13853 fatcat:jque237hijf4jidkp3opgfuch4

Evaluating Neural Machine Translation Using Error Analysis In English -Arabic Texts

فهد بن سعد السهلي
2019 مجلة کلية الآداب جامعة أسوان  
Most of the studies done on machine translation were on rule-based and statistical machine translation rather than neural machine translation.  ...  The aim of this study was to evaluate the output of Neural Machine Translation of translating texts from English into Arabic using error analysis.  ...  As for the machine translation that tackled Arabic language, the first one was a machine translation to translate between English and Arabic and it is dated back to the 1970s where a professor at Harvard  ... 
doi:10.21608/mkasu.2019.212252 fatcat:bo66rxpiajecvi42cob26nobxq

LSTM Neural Reordering Feature for Statistical Machine Translation

Yiming Cui, Shijin Wang, Jianfeng Li
2016 Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies  
Experimental results on NIST OpenMT12 Arabic-English and Chinese-English 1000-best rescoring task show that our LSTM neural reordering feature is robust and achieves significant improvements over various  ...  Artificial neural networks are powerful models, which have been widely applied into many aspects of machine translation, such as language modeling and translation modeling.  ...  Acknowledgments We sincerely thank the anonymous reviewers for their thoughtful comments on our work.  ... 
doi:10.18653/v1/n16-1112 dblp:conf/naacl/CuiWL16 fatcat:o3yodkooa5emffg5qyusr7wfem

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.  ...  Our results is based on NIST MT sets for the year 2005, 2006 and 2012. In the next section, we give a brief introduction to neural machine translation.  ... 
arXiv:1808.06116v1 fatcat:d4jzulum35ehbplg5jzvi3mr5q

A Multitask-Based Neural Machine Translation Model with Part-of-Speech Tags Integration for Arabic Dialects

Laith H. Baniata, Seyoung Park, Seong-Bae Park
2018 Applied Sciences  
Neural Machine Translation (NMT) model.  ...  The proposed solution for NMT is based on the recurrent neural network encoder-decoder NMT model that has been introduced recently.  ...  First, the study investigated the influence of segment-level POS tagging task on Arabic dialect translation.  ... 
doi:10.3390/app8122502 fatcat:pikd3ycupvc23jvhmkphxwbmfq

"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks [article]

Mohammad Sadegh Rasooli, Chris Callison-Burch, Derry Tanti Wijaya
2021 arXiv   pre-print
Our captioning results on Arabic are slightly better than that of its supervised model.  ...  In image captioning, we train a multi-tasking machine translation and image captioning pipeline for Arabic and English from which the Arabic training data is a translated version of the English captioning  ...  Iterative back- translation for neural machine translation. In Pro- ceedings of the 2nd Workshop on Neural Machine Translation and Generation, pages 18-24, Mel- bourne, Australia.  ... 
arXiv:2104.08384v2 fatcat:vswaqg27mve4fpepwuxqzougru

Machine-Translation History and Evolution: Survey for Arabic-English Translations

Nabeel Alsohybe, Neama Dahan, Fadl Ba-Alwi
2017 Current Journal of Applied Science and Technology  
This research is going to contribute to the Machine-Translation area by helping future researchers to have a summary for the Machine-Translation groups of research and to let lights on the importance of  ...  As a result, translation becomes a needed activity in this connected world.  ...  [58] made a comparison between the phrase based machine translation and the neural machine translation and found that they are equal, or the neural one gets somehow higher results than the phrase based  ... 
doi:10.9734/cjast/2017/36124 fatcat:wyc7lka3ovfz5eo66yvl33ir2i

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

Ibrahim Gashaw, Shashirekha
2020 International Journal of Artificial Intelligence & Applications  
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  ...  However, there is no benchmark parallel Amharic-Arabic text corpora available for Machine Translation task.  ...  Machine Translation (HMT), and Neural Machine Translation (NMT).  ... 
doi:10.5121/ijaia.2020.11107 fatcat:5udwbpcbvrah5imcxuzppwpts4

English-Arabic Hybrid Machine Translation System using EBMT and Translation Memory

Rana Ehab, Eslam Amer, Mahmoud Gadallah
2019 International Journal of Advanced Computer Science and Applications  
The availability of a machine translation to translate from English-to-Arabic with high accuracy is not available because of the difficult morphology of the Arabic Language.  ...  To examine the accuracy of the system constructed four experiments were made using Example Based Machine Translation system in the first, Google Translate in the second and Example Based with Google translate  ...  In the first one they used Phrase-based machine translation system and in the second one they used their system [21] .  ... 
doi:10.14569/ijacsa.2019.0100126 fatcat:fub2ord6vzgobchi3twmee3m64

Improving a Multi-Source Neural Machine Translation Model with Corpus Extension for Low-Resource Languages [article]

Gyu-Hyeon Choi, Jong-Hun Shin, Young-Kil Kim
2018 arXiv   pre-print
However, most of the language pairs, such as Korean-Arabic and Korean-Vietnamese, do not have enough resources to train machine translation systems.  ...  We found that the corpus extension could also improve the performance of multi-source neural machine translation.  ...  based on knowledge enhancement)  ... 
arXiv:1709.08898v2 fatcat:hdfrvvdvvfeflbfd5b3gvwnz3q

Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging [article]

Hassan Sajjad, Fahim Dalvi, Nadir Durrani, Ahmed Abdelali, Yonatan Belinkov, Stephan Vogel
2017 arXiv   pre-print
On the tasks of Machine Translation and POS tagging, we found these methods to achieve close to, and occasionally surpass state-of-the-art performance.  ...  In our analysis, we show that a neural machine translation system is sensitive to the ratio of source and target tokens, and a ratio close to 1 or greater, gives optimal performance.  ...  This shows that machine translation involving the Arabic language can achieve competitive results with data-driven segmentation.  ... 
arXiv:1709.00616v1 fatcat:mjmthakudvdavdk4r3jwa7xmzq
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