使用深度学习技术的矿工手语识别和语音翻译

Hridya Dhulipala, Sowmya Hegde, Chaya Hegde, Swetha Gumpena, Geetishree Mishra
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引用次数: 0

摘要

在本文中,我们主要关注使用手语作为地下矿山的最佳沟通手段。为了克服障碍并获得显著的经济效益,深层采矿在高技术和高要求的环境中进行,需要主要的新解决方案和最佳实践,以及增加的安全法规。在这个建议的解决方案中,我们使用图像处理技术来检测和识别手势,并将其转换为音频信息,可以通过无线和无障碍的方式传达给每个工人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sign Language Recognition and Translation to Speech for Mine Workers using Deep Learning Technologies
In this paper, we mainly focus on the use of sign language as an optimal means of communication in underground mines. Deep mining takes place in a highly technical and demanding environment, requiring major new solutions and best practices, as well as increased safety regulations, in order to overcome the hurdles and reap significant economic benefits. In this proposed solution, we use the technology of image processing to detect and recognise hand signs and convert them into audio messages which can be communicated to each worker in a wireless and hassle-free manner.
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