<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Ahmed Ashraf | AI Engineer]]></title><description><![CDATA[Ahmed Ashraf | AI Engineer]]></description><link>https://ahmed-ashraf-ai-engineer.hashnode.dev</link><generator>RSS for Node</generator><lastBuildDate>Tue, 22 Sep 2026 16:16:05 GMT</lastBuildDate><atom:link href="https://ahmed-ashraf-ai-engineer.hashnode.dev/rss.xml" rel="self" type="application/rss+xml"/><language><![CDATA[en]]></language><ttl>60</ttl><item><title><![CDATA[AI-Powered Real-Time Egyptian Sign Language Translator]]></title><description><![CDATA[Developed by:*Ahmed Ashraf and Mohamed Ibrahim, AI Engineers.*
Communication barriers are a daily challenge for the Deaf and Hard-of-Hearing community in Egypt. To address this, we developed a real-time Egyptian Sign Language (ESL) translator using A...]]></description><link>https://ahmed-ashraf-ai-engineer.hashnode.dev/ai-powered-real-time-egyptian-sign-language-translator-1</link><guid isPermaLink="true">https://ahmed-ashraf-ai-engineer.hashnode.dev/ai-powered-real-time-egyptian-sign-language-translator-1</guid><category><![CDATA[AI]]></category><category><![CDATA[Computer Vision]]></category><category><![CDATA[Deep Learning]]></category><dc:creator><![CDATA[Ahmed Ashraf]]></dc:creator><pubDate>Wed, 31 Dec 2025 21:18:23 GMT</pubDate><enclosure url="https://cdn.hashnode.com/res/hashnode/image/upload/v1767215721546/dc515040-0a38-409b-905c-150c945e73b9.png" length="0" type="image/jpeg"/><content:encoded><![CDATA[<h3 id="heading-developed-byahmed-ashraf-and-mohamed-ibrahim-ai-engineers"><strong>Developed by:*</strong>Ahmed Ashraf and Mohamed Ibrahim, AI Engineers.*</h3>
<p>Communication barriers are a daily challenge for the Deaf and Hard-of-Hearing community in Egypt. To address this, we developed a <strong>real-time Egyptian Sign Language (ESL) translator</strong> using <strong>AI and computer vision</strong>.</p>
<p>Unlike traditional gesture classifiers, our system processes <strong>continuous sequences of hand, body, and facial movements</strong>, producing fluent <strong>Arabic text</strong> and optional <strong>speech output</strong>. Key highlights:</p>
<ul>
<li><p><strong>Real-Time Recognition:</strong> Uses MediaPipe Holistic for hands, face, and body landmarks</p>
</li>
<li><p><strong>Sequence Modeling:</strong> Two-layer Bidirectional LSTM captures gesture sequences</p>
</li>
<li><p><strong>Context-Aware Translation:</strong> Combines gestures into meaningful Arabic phrases</p>
</li>
<li><p><strong>Accessible UI:</strong> Instant predictions with optional Text-to-Speech</p>
</li>
</ul>
<p>We built a <strong>custom ESL dataset</strong> of 400 signs, and the model achieves <strong>97% test accuracy</strong> in real-time inference.</p>
<p>This project demonstrates how <strong>AI can break communication barriers</strong> and empower the Deaf community in Egypt.</p>
<p>📖 Read the full story and see screenshots here<br />Medium Article: <a target="_blank" href="https://ahmedashrafmo.medium.com/real-time-egyptian-sign-language-translator-ai-powered-solution-to-empower-the-deaf-community-in-727430624b1c">Medium</a><a target="_blank" href="https://lnkd.in/dFbU--Gx%EF%BF%BCTowards">  
</a>Towards AI: <a target="_blank" href="https://pub.towardsai.net/ai-powered-real-time-egyptian-sign-language-translator-2caf5e7eb28f">Towards AI</a></p>
<p><a target="_blank" href="https://lnkd.in/d89n5VZc"><strong>License:</strong><br /><strong>© 2025 Ahmed</strong></a> <strong>Ashraf.</strong> "Real-Time Egyptian Sign Language Translator" content (articles, tutorials, screenshots, diagrams) is licensed under CC BY-NC-ND 4.0.</p>
<p>You may share this work, but must:<br /><strong>- Give credit to Ahmed Ashraf</strong><br /><strong>- Not use commercially</strong><br /><strong>- Not modify or create derivatives</strong></p>
<p><strong>Full license:</strong> <a target="_blank" href="https://creativecommons.org/licenses/by-nc-nd/4.0/"><strong>https://creativecommons.org/licenses/by-nc-nd/4.0/</strong></a></p>
]]></content:encoded></item><item><title><![CDATA[AI-Powered Real-Time Egyptian Sign Language Translator]]></title><description><![CDATA[Communication barriers are a daily challenge for the Deaf and Hard-of-Hearing community in Egypt. To address this, we developed a real-time Egyptian Sign Language (ESL) translator using AI and computer vision.
Unlike traditional gesture classifiers, ...]]></description><link>https://ahmed-ashraf-ai-engineer.hashnode.dev/ai-powered-real-time-egyptian-sign-language-translator</link><guid isPermaLink="true">https://ahmed-ashraf-ai-engineer.hashnode.dev/ai-powered-real-time-egyptian-sign-language-translator</guid><category><![CDATA[AI]]></category><category><![CDATA[Deep Learning]]></category><category><![CDATA[Computer Vision]]></category><category><![CDATA[sign language]]></category><category><![CDATA[Accessibility]]></category><dc:creator><![CDATA[Ahmed Ashraf]]></dc:creator><pubDate>Wed, 31 Dec 2025 21:04:27 GMT</pubDate><enclosure url="https://cdn.hashnode.com/res/hashnode/image/upload/v1767214567112/31c53c52-06f1-4625-9bef-295b46e6062f.png" length="0" type="image/jpeg"/><content:encoded><![CDATA[<p>Communication barriers are a daily challenge for the Deaf and Hard-of-Hearing community in Egypt. To address this, we developed a <strong>real-time Egyptian Sign Language (ESL) translator</strong> using <strong>AI and computer vision</strong>.</p>
<p>Unlike traditional gesture classifiers, our system processes <strong>continuous sequences of hand, body, and facial movements</strong>, producing fluent <strong>Arabic text</strong> and optional <strong>speech output</strong>. Key highlights:</p>
<ul>
<li><p><strong>Real-Time Recognition:</strong> Uses MediaPipe Holistic for hands, face, and body landmarks</p>
</li>
<li><p><strong>Sequence Modeling:</strong> Two-layer Bidirectional LSTM captures gesture sequences</p>
</li>
<li><p><strong>Context-Aware Translation:</strong> Combines gestures into meaningful Arabic phrases</p>
</li>
<li><p><strong>Accessible UI:</strong> Instant predictions with optional Text-to-Speech</p>
</li>
</ul>
<p>We built a <strong>custom ESL dataset</strong> of 400 signs, and the model achieves <strong>97% test accuracy</strong> in real-time inference.</p>
<p>This project demonstrates how <strong>AI can break communication barriers</strong> and empower the Deaf community in Egypt.</p>
<p>👉 Read the full article on Medium: [<a target="_blank" href="https://ahmedashrafmo.medium.com/real-time-egyptian-sign-language-translator-ai-powered-solution-to-empower-the-deaf-community-in-727430624b1c?postPublishedType=repub">Medium Link</a>]</p>
]]></content:encoded></item></channel></rss>