Bridging the gap between sign language and spoken language through AI-driven innovation.
Our system uses advanced AI and computer vision to interpret British Sign Language (BSL) gestures, converting them into real-time text and speech output.
By leveraging machine learning models, deep learning, and natural language processing, we ensure accurate, real-time sign recognition that can be used in various applications, from accessibility tools to customer support solutions.
We use deep learning models to recognize hand gestures, powered by TensorFlow & PyTorch.
Our system utilizes OpenCV & MediaPipe to detect and track hand movements with high accuracy.
We integrate Google Speech API and Whisper AI to ensure natural speech synthesis.
| Component | Technology Used |
|---|---|
| Programming Languages | Python, JavaScript |
| Machine Learning Models | TensorFlow, PyTorch |
| Computer Vision | OpenCV, MediaPipe |
| Backend | Flask, FastAPI |
| Frontend | React, Bootstrap |
| Speech-to-Text | Google Speech API, OpenAI Whisper |
| Deployment | AWS, Azure |