This Sign Language Translator is a machine learning-based system that enables real-time translation of sign language gestures into spoken or written language. Using Convolutional Neural Networks (CNNs) and advanced machine learning techniques, this project aims to bridge the communication gap between individuals who are deaf or hard of hearing and those who do not understand sign language.
The translator system leverages computer vision algorithms to accurately recognize and interpret a wide range of sign language gestures.
Built using Python programming language and libraries such as TensorFlow, OpenCV, and NumPy, this project offers a customizable user interface that allows users to select their preferred output format.
This Sign Language Translator project aims to make sign language more accessible, empowering individuals with hearing impairments and promoting inclusivity in communication.