首页> 外文期刊>Assistive technology: the official journal of RESNA >A Kinect-Based Sign Language Hand Gesture Recognition System for Hearing- and Speech-Impaired: A Pilot Study of Pakistani Sign Language
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A Kinect-Based Sign Language Hand Gesture Recognition System for Hearing- and Speech-Impaired: A Pilot Study of Pakistani Sign Language

机译:基于Kinect的听觉和言语障碍者手势手势识别系统:巴基斯坦手语的初步研究

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摘要

Sign language provides hearing and speech impaired individuals with an interface to communicate with other members of the society. Unfortunately, sign language is not understood by most of the common people. For this, a gadget based on image processing and pattern recognition can provide with a vital aid for detecting and translating sign language into a vocal language. This work presents a system for detecting and understanding the sign language gestures by a custom built software tool and later translating the gesture into a vocal language. For the purpose of recognizing a particular gesture, the system employs a Dynamic Time Warping (DTW) algorithm and an off-the-shelf software tool is employed for vocal language generation. Microsoft (R) Kinect is the primary tool used to capture video stream of a user. The proposed method is capable of successfully detecting gestures stored in the dictionary with an accuracy of 91%. The proposed system has the ability to define and add custom made gestures. Based on an experiment in which 10 individuals with impairments used the system to communicate with 5 people with no disability, 87% agreed that the system was useful.
机译:手语为听力和言语受损的人提供了与社会其他成员进行交流的界面。不幸的是,大多数普通人并不理解手语。为此,基于图像处理和模式识别的小工具可以为检测手语并将其翻译为语音提供重要帮助。这项工作提出了一种系统,该系统可通过定制的软件工具来检测和理解手语手势,然后将手势翻译成语音。为了识别特定手势,该系统采用了动态时间规整(DTW)算法,并且采用了现成的软件工具来生成语音。 Microsoft(R)Kinect是用于捕获用户视频流的主要工具。所提出的方法能够以91%的精度成功检测字典中存储的手势。所提出的系统具有定义和添加定制手势的能力。根据一项实验,其中有10位残障人士使用该系统与5位无障碍人士进行交流,有87%的人认为该系统很有用。

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