@article {Moumen20211634,
	title = {Real-time Arabic scene text detection using fully convolutional neural networks},
	journal = {International Journal of Electrical and Computer Engineering},
	volume = {11},
	number = {2},
	year = {2021},
	note = {cited By 1},
	pages = {1634-1640},
	abstract = {The aim of this research is to propose a fully convolutional approach to address the problem of real-time scene text detection for Arabic language. Text detection is performed using a two-steps multi-scale approach. The first step uses light-weighted fully convolutional network: TextBlockDetector FCN, an adaptation of VGG-16 to eliminate non-textual elements, localize wide scale text and give text scale estimation. The second step determines narrow scale range of text using fully convolutional network for maximum performance. To evaluate the system, we confront the results of the framework to the results obtained with single VGG-16 fully deployed for text detection in one-shot; in addition to previous results in the state-of-the-art. For training and testing, we initiate a dataset of 575 images manually processed along with data augmentation to enrich training process. The system scores a precision of 0.651 vs 0.64 in the state-of-the-art and an FPS of 24.3 vs 31.7 for a VGG-16 fully deployed. {\textcopyright} 2021 Institute of Advanced Engineering and Science. All rights reserved.},
	doi = {10.11591/ijece.v11i2.pp1634-1640},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097836850\&doi=10.11591\%2fijece.v11i2.pp1634-1640\&partnerID=40\&md5=18f6883629a31b869bc0f2225a4cbf29},
	author = {Moumen, R. and Chiheb, R. and Faizi, R.}
}
@article {Moumen2019369,
	title = {An NLP based text-to-speech synthesizer for Moroccan Arabic},
	journal = {Lecture Notes in Networks and Systems},
	volume = {49},
	year = {2019},
	note = {cited By 0},
	pages = {369-379},
	doi = {10.1007/978-3-319-97719-5_23},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063269452\&doi=10.1007\%2f978-3-319-97719-5_23\&partnerID=40\&md5=0696f7563e81ff83ad6826ed84e31cef},
	author = {Moumen, R. and Chiheb, R.}
}
@conference {Moumen2018,
	title = {Arabic diacritization with gated recurrent unit},
	booktitle = {ACM International Conference Proceeding Series},
	year = {2018},
	doi = {10.1145/3230905.3230931},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053484931\&doi=10.1145\%2f3230905.3230931\&partnerID=40\&md5=3a401539dc4a1f24a5a97d1b3fdc8e36},
	author = {Moumen, R. and Chiheb, R. and Afia, A.E. and Faizi, R.}
}
@article {Moumen2018360,
	title = {Evaluation of gated recurrent unit in Arabic diacritization},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {9},
	number = {11},
	year = {2018},
	pages = {360-364},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059029808\&partnerID=40\&md5=8ec6347667792a079047e6121cfd5999},
	author = {Moumen, R. and Chiheb, R. and Faizi, R. and El Afia, A.}
}
@conference {Moumen20181,
	title = {An NLP based text-to-speech synthesizer for Moroccan Arabic},
	booktitle = {Proceedings of 2017 International Conference of Cloud Computing Technologies and Applications, CloudTech 2017},
	volume = {2018-January},
	year = {2018},
	pages = {1-5},
	doi = {10.1109/CloudTech.2017.8284745},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046676982\&doi=10.1109\%2fCloudTech.2017.8284745\&partnerID=40\&md5=9ca745be5c63a00cda019ef8b0230a9d},
	author = {Moumen, R. and Chiheb, R. and Faizi, R. and Afia, A.E.}
}
@conference {Moumen2017,
	title = {A novel text-to-speech synthesizer for processing sms in moroccan Arabic},
	booktitle = {Proceedings of International Conference on Computers and Industrial Engineering, CIE},
	year = {2017},
	note = {cited By 0},
	abstract = {This paper proposes a novel text-to-speech (TTS) system that converts text messages (SMS) into speech sequences. This system takes into consideration the characteristics of the Moroccan context, where several languages might be used in the same text message. Therefore, the languages that are analyzed in this work are English, French, Moroccan Arabic and Modern Standard Arabic (MSA). Processing French, English, or Modern Standard Arabic is common and has given satisfying results. However, Moroccan Arabic remains under-studied for many reasons, particularly the lack of data resources given that this Arabic dialect is primarily spoken and non-codified.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040947811\&partnerID=40\&md5=1ddd4fb5d94d0350d8211d7bc3fc7c61},
	author = {Moumen, R. and Chiheb, R. and Zarra, T. and Faizi, R. and El Afia, A.}
}
