Sign Language Recognition for Needy People Using Machine Learning Model

Abstract

In this digital era, gesture identification is one of the revolutions to serve specially-abled (deaf and dumb) people, and it is been investigated for several decades. Tactlessly, all research studies have their restrictions and are incompetent to be used commercial. Few studies have been recognized to be effective for gesture identification, but it needs an affluent cost to be marketed. Currently, research scholars have more consideration for developing gesture identification systems that can be used commercially. Scholars do their studies in innumerable ways. It twitches from the data gaining approaches when required. The data gaining approach differs since the cost is required for a decent device, but a low-cost device is needed for the hand gesture identification system to be made saleable. Approaches used in implementing the system are diverse between studies. Separately, approach has its strong point compared to other approach and research still using different approaches in developing their gesture identification. Every approach has setbacks compared to others. This manuscript intends to review the gesture identification system for needy people. Hence, other studies can get more information about the approaches used and develop better applications in the forthcoming.