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Conversion of Tactile Sign Language into English for Deaf/Dumb Interaction

机译:触觉手语转换为英语的聋/哑互动

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摘要

Natural language is the way of communication for normal human beings which includes spoken language, written and body gestures i.e. head gesture, hand gestures, facial expressions and lip motion etc. On the other hand, speech and hearing-impaired people uses sign language for communication which is not understandable for normal people thus they face problems of communication in society. In this problem interpreters are required but the human interpreters are costly and are not an efficient solution. Thus, there is a need of system which will translate the sign language into normal language which will be understandable by normal. The system proposed and explained in the paper is an efficient solution to this problem. In the system, sign recognition is done using CAMSHIFT and P2DHHM algorithm followed by Haar Cascade Classifier. After sign recognition, the language technology techniques of POS tagging and LALR parser are used to convert recognized sign words into English sentence. Till date no any system has worked on sentence framing. Results shows that this system produces 92% of accurate result which will bridge the gap between impaired and Normal people.
机译:自然语言是普通人类的交流方式,包括口头语言,书面手势和身体手势,例如头部手势,手势,面部表情和嘴唇动作等。另一方面,语音和听力受损的人使用手语进行交流这是普通人无法理解的,因此他们面临着社会沟通的问题。在这个问题中,需要口译员,但是人工口译员很昂贵,而且不是有效的解决方案。因此,需要一种将手语翻译成普通语言的系统,该普通语言可以被普通人理解。本文提出和解释的系统是解决此问题的有效方法。在系统中,使用CAMSHIFT和P2DHHM算法以及Haar级联分类器进行符号识别。符号识别后,使用POS标记和LALR解析器的语言技术将识别的符号词转换为英语句子。到目前为止,还没有任何系统在句子框架方面起作用。结果表明,该系统可产生92%的准确结果,从而弥合了残障人士和正常人之间的鸿沟。

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