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Humans communicate with each other through natural language, such as speech and written words. However for the deaf people, the sign language is the only means of conveying information. Without an interpreter, they are unable to converged with each other. Because of this, the implementation of a technology that understands sign language would be of significant help to the social lives of deaf people. Indian sign language (ISL) uses both hands to make gestures instead of one hand unlike ASL. The suggested approach is to develop an ISL recognition system which converts the sign language into readable text. This can be done by various approaches like smart gloves, object detection and pose detection. The proposed method uses a tensorflow object detection for detecting hand moments. Mobile-net is used yo extract feature with the help of and further detection by using single shot multi-box detection (SSD). The system can able to detect 26 of 26 ISL signs in real time with mAP score 96.1 %
Sonkamble et al. (Thu,) studied this question.
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