Sign Language Recognition-A Survey of Techniques
Udit Barde1, Archana Ghotkar2
1Udit Barde, Computer Engineering, Pune Institute of Computer Technology, Pune, India.
2Archana Ghotkar, Computer Engineering, Pune Institute of Computer Technology, Pune, India.
Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 854-857 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3925079220/2020©BEIESP | DOI: 10.35940/ijrte.B3925.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Sign language is the only method of communication for the hearing and speech impaired people around the world. Most of the speech and hearing-impaired people understand single sign language. Thus, there is an increasing demand for sign language interpreters. For regular people learning sign language is difficult, and for speech and hearing-impaired person, learning spoken language is impossible. There is a lot of research being done in the domain of automatic sign language recognition. Different methods such as, computer vision, data glove, depth sensors can be used to train a computer to interpret sign language. The interpretation is being done from sign to text, text to sign, speech to sign and sign to speech. Different countries use different sign languages, the signers of different sign languages are unable to communicate with each other. Analyzing the characteristic features of gestures provides insights about the sign language, some common features in sign languages gestures will help in designing a sign language recognition system. This type of system will help in reducing the communication gap between sign language users and spoken language users.
Keywords: American Sign Language, gesture recognition, Indian Sign language, sign language recognition, Sign language translation.