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作 者:Muhammad Sanaullah Muhammad Kashif Babar Ahmad Tauqeer Safdar Mehdi Hassan Mohd Hilmi Hasan Amir Haider
机构地区:[1]Bahauddin Zakariya University,Department of Computer Science,Multan,60,000,Pakistan [2]Air University,Department of Computer Science,Multan,60,000,Pakistan [3]Air University,Department of Computer Science,Islamabad,44,000,Pakistan [4]Centre for Research in Data Science,Department of Computer and Information Sciences,Universiti Teknologi PETRONAS,Seri Iskandar,32610,Perak,Malaysia [5]Department of Intelligent Mechatronics Engineering,Sejong University,Seoul,05006,Korea
出 处:《Computers, Materials & Continua》2022年第8期2501-2519,共19页计算机、材料和连续体(英文)
基 金:The work presented in this paper is part of an ongoing research funded by Yayasan Universiti Teknologi PETRONAS Grant(015LC0-311 and 015LC0-029).
摘 要:Communication is a basic need of every human being to exchange thoughts and interact with the society.Acute peoples usually confab through different spoken languages,whereas deaf people cannot do so.Therefore,the Sign Language(SL)is the communication medium of such people for their conversation and interaction with the society.The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs.The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively.The signs for singular words such as I,eat,drink,home are unalike the plural words as school,cars,players.A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately.Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration.The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment.Hence,there is still a demand for specific environment to automate such a communication solution to interact with such type of special people.This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words.Finally,these are converted into the respective words/sentences within a reasonable time.This provide a real time solution for the deaf people to communicate and interact with the society.
关 键 词:Sign language machine learning conventional neural network image processing deaf community
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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