A Survey on Sign Language Recognition with Video Chat

The use of sign language is a crucial tool for improving communi- cation between hearing-impaired people and the general public. SLR (Sign Language Recognition) systems in past have been sophisticated challenging to train. However, this research, we provide novel method that makes SSD MobileNet V2 FPNLite 320x320 pre-trained models object recognition based on TensorFlow's detection. By enabling identification detection set images, streamlines train- ing process. suggested system will be trained evaluated using 10 15 different American Sign symbols. A fun- damental social skill used exchange information communica- tion. It frequently express oneself fulfill funda- mental human needs including desire protection, safety, connection. Several stages, diverse methods, distinct conse- quences are procedure. typically refers two-way local vicinity touch. Information flows far more easily when speaking same than they languages from lan- guage families. In order facilitate video chat communication be- tween signers non-signers, our proposed recog- nition specifically created. Each peer can see hear other during conversation thanks their individual cameras microphones. Nevertheless, method, spe- cific also view indicators end exhibits or copies. Our employs recognize track signer's hand motions real-time accomplish this. technology then over- lays graphic detected onto non-video feed. This overlay positioned so it does not obstruct signer by non-signer obtrusive. contem- porary technology, solution made enable distant non-signers. With help system, im- proved, allowing non-signers communicate in- teract effectively. Index Terms— SLR(Sign Recognition), Video Chat, Object Detection, MobileNet.