Glove-based sign language recognition solution to assist communication for deaf users

Jose Emiliano Lopez-Noriega, Miguel Ivan Fernandez-Valladares, Víctor Uc Cetina
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引用次数: 10

Abstract

This manuscript presents the research and development of a software that help deaf-mute communication by identifying the position of the fingers of the hand with 5DT gloves. The sign language is adopted by nearly all people with hearing deficiency, making it their main form of communication, but this communication is only successfully achieved if all the participants of the conversation are familiar with the sign language. The goal is to be able to translate hand signs into words and phrases with the possibility to send audio signals to allow deaf-mute users to communicate to people not familiar with the sign language. The recognition of hand gestures is accomplished using a neural network tested using five different training algorithms. A cross-validation experiment is provided to illustrate the robustness of our methods.
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基于手套的手语识别解决方案,帮助聋人交流
本文介绍了一种软件的研究和开发,该软件通过使用5DT手套识别手部手指的位置来帮助聋哑人进行交流。几乎所有的听障人士都使用手语,使之成为他们主要的交流方式,但这种交流只有在对话的所有参与者都熟悉手语的情况下才能成功地实现。其目标是能够将手语翻译成单词和短语,并有可能发送音频信号,让聋哑人与不熟悉手语的人交流。手势的识别是通过使用五种不同的训练算法测试的神经网络来完成的。交叉验证实验说明了我们的方法的稳健性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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