Loading repository data…
RhythmusByte / repository
Sign-Language-to-Speech
Real-time ASL interpreter using OpenCV and TensorFlow/Keras for hand gesture recognition. Features custom hand tracking, image preprocessing, and gesture classification to translate American Sign Language into text and speech output. Built with accessibility in mind.
#asl#assistive-technology#cv2#hand-tracking#handdetection#image-classification
Live repository statistics
★ 10Stars
⑂ 0Forks
◯ 0Open issues
◉ 10Watchers
59/100
OPENREPOHUB HEALTH SIGNAL
Mixed signals
A transparent discovery signal based on current public GitHub metadata.
Recent activity35% weight
52
Community adoption25% weight
15
Maintenance state20% weight
100
License clarity10% weight
100
Project information10% weight
75
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
README preview
🎯 Project Overview
Sign Language to Speech Conversion is a real-time American Sign Language (ASL) recognition system powered by computer vision and deep learning. It translates ASL hand gestures into both text and speech output, enhancing accessibility and communication.
📖 For installation, architecture, usage, and contribution guidelines, visit the Project Wiki.
✨ Key Features
- 🔮 Real-time hand detection & gesture tracking
- 🧠 CNN-based classification using TensorFlow/Keras
- 🔊 Simultaneous text & speech output
- 📢 Designed for accessibility & inclusivity
📊 System Architecture
| Level 0 | Level 1 | Level 2 |
|---|---|---|
For details on Data Flow Diagrams (DFD), Use Case Diagrams, and System Design, check the Architecture Section in the Wiki.
🛠 Tech Stack
Core Technologies
