GESTURE LANGUAGE TRANSLATOR

This paper presents a Gesture Language Translator system that aims at bringing the solution to the effective communication between hearing-impaired and people who do not understand sign language. Sign language uses gestures and facial expressions, which are not general knowledge, and hence communication between hearing-impaired or deaf and mute people becomes difficult. To solve this problem, we have created a website that interprets sign language into verbal language, thus it is easy to communicate between people. This system utilizes Computer Vision and Machine Learning (ML) algorithms to identify and interpret different sign language movements accurately. The system is designed to interpret and classify the hand movements using an advanced ML model to provide accurate interpretation. We have also included a feature named “Sign Image,” which shows the sign language image of a word. This adds a new level of experience for the user by visually checking the interpretation. An important feature of our system for the ease of use, the users can converse with the system using both Image-based and text-based questions. We utilize AI for Image-to-text feature to enable the users to use for questions. Then, we use Google Text-to-Image to transcribe the AI response created into visual form to facilitate communication.