Sign Language Barriers In Communication

Abstract — Speech plays a basic role in communication between people, in education, in sharing ideas and in maintaining social contacts. The Speech-impaired have to challenge communication barriers in a mostly speech-capable society. Many ways of communications are used between human and computer, one of them includes using gesture which is considered to be one of the most natural ways in a virtual reality system. With information technology development in our society, we can expect that embedment of computers will be larger in environment. These environments will have needs of new types of human computer-interaction that are natural and easy to use. However, they are not that convenient to people and are un-natural. The hand gestures are used

It will also implement signs that can be converted to speech. Thus the application will solve the problem of communication by letting the speech impaired people make sings in front of a web cam and thus produces a resultant voice output. Sign recognition is a typical applies of image understanding as it involves capturing, detecting and recognizing of hand signs. A functioning sign language recognition system could provide an opportunity for the speech impaired to communicate with non-signing people without the need for an interpreter. It could be used to generate speech or text making the speech impaired more independent . Unfortunately there has is a little know in this field. In this work our aim is to develop a Sign Language Recognition system which is restricted to finger spelling. The implementation includes the use of a webcam that captures live images which is given to an application built in Visual Studio using OpenCV library. Signs are captured using webcam which is then tested with the samples of trained images using neural network classifier, the match then gives the resultant text output to the system and later reading out the text using a text to speech convertor. This work is an attempt to bringing down the barrier of communication and let the speech impaired communicate efficiently, thus encouraging a two way communication

Different methods have been proposed for acquiring information necessary for recognition gestures system . Some methods used additional hardware devices such as data glove devices and color markers to easily extract comprehensive description of gesture features . To exploit the use of gestures in HCI it is necessary to provide the means by which they can be interpreted by computers. The HCI interpretation of gestures requires that dynamic and/or static configurations of the human hand, arm, and even other parts of the human body, be measurable by the machine. First attempts to solve this problem resulted in mechanical devices that directly measure hand and/or arm joint angles and spatial position. This group is best represented by the so-called glove-based devices. Glove-based gestural interfaces require the user to wear a cumbersome device, and generally carry a load of cables that connect the device to a computer. This hinders the ease and naturalness with which the user can interact with the computer controlled environment. Other methods based on the appearance of the hand using the skin color to segment the hand and extract necessary features, these methods considered easy, natural and less cost comparing with methods mentioned before. Some recent reviews explained gesture