Real Time Sign Language Translator for Speech Impaired

The project develops a real-time sign language translation system using computer vision and machine learning to bridge communication gaps for speech-impaired individuals. Utilizing real-time gesture recognition with frameworks like MediaPipe, the system interprets hand movements accurately and translates them into text. Additionally, integrating text-to-speech APIs facilitates seamless audio processing for dynamic communication in various settings. Aiming for inclusivity in educational and professional environments, the project will deliver a user-friendly interface that caters to individuals of all ages and technological backgrounds, ultimately fostering a more inclusive society.