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