👐 SignComm – AI-Powered Sign Language Translator

Bridging Silence with Intelligence SignComm is an AI-driven real-time sign language translator designed to break down the communication barriers faced by the deaf and mute community. By combining computer vision, deep learning, and generative AI, it enables seamless two-way communication between signers and non-signers.

💡 Inspiration

Imagine standing in a classroom, hospital, or job interview and being unable to express yourself because no one understands sign language. Millions experience this every day.

SignComm was born out of a simple yet powerful idea: What if AI could serve as the universal interpreter, enabling the deaf and mute to be heard instantly, everywhere?

---

🚨 The Problem

• Over 70 million people worldwide use sign language as their primary means of communication.
• Less than 1% of the global population understands it.
• Hiring interpreters is expensive and limited.
• Existing solutions are either hardware-heavy, inaccurate, or non-scalable.

This results in a Communication Divide—barriers in education, healthcare, employment, and social participation.

---

🌍 Our Solution – SignComm

SignComm is a real-time, AI-powered translator that:

• Detects hand gestures via webcam.
• Converts signs into text and speech.
• Translates voice back into sign animations.
• Supports multi-language translation with contextual accuracy using Gemini AI.

It’s low-cost, scalable, and accessible—a bridge that empowers communication without boundaries.

---

🚀 Tech Stack

🔧 Core Technologies

Technology	Role
HTML, CSS, JS	Frontend interface for accessibility and responsiveness
Flask	Backend framework to serve ML models
TensorFlow (DNN)	Deep learning models for gesture recognition
OpenCV	Real-time image capture & preprocessing
Firebase	Authentication & user data storage
Gemini AI	Contextual translation and multi-language refinement

---

🌟 Features

✅ Real-Time Gesture Recognition – Instant sign-to-text conversion via webcam ✅ Speech-to-Sign – Converts spoken language into sign animations ✅ Multi-Language Support – Translate into English, Tamil, Hindi, and more ✅ Custom Gesture Library – Add & train new gestures for flexibility ✅ Lightweight & Low-Cost – Runs on basic devices without specialized hardware

---

🧠 How It Works

1. Capture – User’s hand signs are captured via webcam.
2. Preprocess – OpenCV filters and extracts key features.
3. Classify – TensorFlow DNN model predicts the gesture.
4. Translate – Gemini AI enhances contextual meaning and supports multiple languages.
5. Output – Translated result is shown as text, speech, or animation.

flowchart TD
A[Hand Gesture Input] --> B(OpenCV Preprocessing)
B --> C(TensorFlow DNN Classification)
C --> D{Gemini AI Translation}
D --> E[Text Output]
D --> F[Voice Output]
D --> G[Sign Animation]

Loading

---

🖼️ Screenshots

---

🧪 Run Locally

1. Clone the repository

   git clone https://github.com/Phoenixarjun/SignComm
   cd SignComm

2. Install dependencies

   pip install -r requirements.txt

3. Add credentials

   FIREBASE_API_KEY=your_key
   GEMINI_API_KEY=your_key

4. Start server

   python app.py

5. Open index.html in your browser 🎉

---

📊 Impact & Future Scope

🔹 Impact

• Makes education, healthcare, and workplaces inclusive
• Reduces reliance on interpreters
• Scales across regions with multilingual adaptability

🔹 Future Scope

• Mobile App with offline mode
• AR/VR gloves for more natural sign capture
• Integration with wearables (smart glasses for subtitles)
• Global Sign Database with community-driven expansion
• Alignment with UN SDG #10 – Reduced Inequalities

---

👨‍💻 Author

Naresh B A | 💻 Full Stack & AI/ML Enthusiast | 🚀 Innovator

• 🌐 Portfolio
• 💼 LinkedIn

---

⚡ Closing Note

“SignComm is more than technology it’s empathy coded into algorithms. We’re not just translating signs; we’re amplifying voices.”