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Journal of Electrical Electronics Engineering(JEEE)

ISSN: 2834-4928 | DOI: 10.33140/JEEE

Impact Factor: 1.2

A Voice-Activated, Deep-Learning-Based Emergency Alarm for Arabic Dialects

Abstract

Mohammed Z. Al Zahrani, Helal J. Al Malki, Saud S. Al Lahyani, Ali A. Al Zahrani, Khalid O. Al Malki, Ahmad Z. Hasanain, Mirza I. Yunus, Ashraf M. Khalifa, Mohammed M. Almatrafi

In this report, we will talk in almost every detail about our project, in order to cover most aspects of the project. We tried as much as possible to make the report suitable for two segments, the specialists and the public so that the reader can make the most of the report.

We will talk about the hardware and software used in the project and how they work, in order to explain to the ordinary reader how some technical matters are done and to explain to the specialist some things that he or she might consider while developing. In our project, samples are the cornerstone of the project, and for this, we have focused on them in the report, from the methods of identifying samples to access to taking samples and analyzing them project to other dimensions. When we wrote the project, we took into account that development on the project is an important part of this academic process, so we paved the way for those who want to develop by collecting our own database in Arabic for scientific purposes so that development on it becomes easier and more productive.

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