DualSign is a bidirectional translation system designed to convert text to sign language and vice versa. This project leverages Natural Language Processing (NLP) and digital image processing to bridge the communication gap between sign language users and non-sign language users. The system enables real-time conversion, facilitating seamless and accessible communication.
Text-to-Sign Translation: Converts user-entered text into sign language using a digital interface with sign visuals or animations. Sign-to-Text Translation: Recognizes and processes input gestures (e.g., via webcam) to generate text translations using advanced image processing techniques. Interactive Interface: User-friendly design for accessibility and ease of use. Real-Time Processing: Quick and efficient translation with minimal latency.
Programming Language:
- Python
Frameworks and Libraries:
- OpenCV (image and video processing)
- NumPy (numerical computations)
- TensorFlow/Keras (optional, for gesture recognition models)
- NLTK/Spacy (for NLP-based text processing)
Hardware Requirements
- Webcam: For capturing sign gestures.
- GPU Support: Optional, for accelerated machine learning inference.