A novel technique of sign language recognition system using machine learning for differently abled person

Khan Rabia, H. Rashid, Kumar Tyagi Rajesh, Singh Juhi
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Abstract

Sign language is a language used by deaf and dumb people to communicate through hand gestures or facial expressions combined with non-manual elements. Various automotive tools and software have been developed by many developers, but they require hardware and an Internet connection, which adds to the cost of the software. In this paper, the presented software captures the hand gesture, and with the help of various machine learning optimization algorithms such as Stochastic Gradient Descent (SGD) and Adam (optimizer), the accuracy will be determined to give predictive value. With the help of computers, it could be a new way of learning for deaf and dumb people. During such a pandemic, various group learning apps and software have been developed for the purpose of conducting online classes, but they are useful for ordinary people. Using this technique will help deaf and dumb people with online learning.
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一种基于机器学习的残疾人手语识别系统新技术
手语是聋哑人通过手势或面部表情结合非手势元素进行交流的语言。许多开发人员已经开发了各种各样的汽车工具和软件,但它们需要硬件和互联网连接,这增加了软件的成本。在本文中,所提出的软件捕获手势,并借助各种机器学习优化算法,如随机梯度下降(SGD)和Adam(优化器),确定精度以给出预测值。在计算机的帮助下,它可能成为聋哑人学习的一种新方式。在新冠肺炎疫情期间,虽然开发了各种以在线授课为目的的小组学习应用程序和软件,但这些应用程序和软件对普通人来说是有用的。使用这种技术将帮助聋哑人进行在线学习。
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