Project Overview

The Sign Language to Speech Conversion project is a real-time system designed to bridge communication gaps for individuals with hearing and speech impairments. The system captures sign language gestures via a camera, processes them using advanced computer vision and deep learning techniques, and then translates the gestures into both text and audible speech.

Abstract:
This project presents an advanced sign language-to-speech conversion system developed to empower users by enabling independent communication. Utilizing a real-time camera interface, the system processes hand gestures through a Convolutional Neural Network (CNN) built with TensorFlow/Keras. The resulting output—both textual and speech—is intended to enhance accessibility in social, educational, and professional settings.