Sign Language Detection and Translation in Speech
Abstract
Communication is a fundamental form of human interaction, but sometimes it becomes inconvenient, problematic and expensive for deaf-mute people to communicate with nonASL speakers. This paper aims to bridge the communication gap between people with inability to speak and Non-ASL speakers to communicate conveniently. In the current work, we developed a smart glove which detects gestures using flex sensors and accelerometer/gyro-meter to detect the motion of hand in space. The experimental results implies that system is accurate and cost effective. The gestures are then mapped to a database of supervised data using KNN algorithm to recognize English alphabets, numbers and basic sentences.
References
www.asianssr.org ID: 436
[5] https://itp.nyu.edu/archive/physcompspring2014/sensors/Reports/Flex.html [6] Roman Akozak www.romanakozak.com/signlanguagetranslator [7] D. Quick. (2012, July 12). “Sign language-to-speech translating gloves take out Microsoft Imagine Cup 2012” [Online]. Available: http://www.gizmag.com/enabletalk-sign-language-gloves/23268/ [8] Ravikiran, J., Kavi, M., Suhas, M., Sudheender, and S., Nitin, V. “Finger Detection for Sign Language Recognition”, Proceedings of the International multi conference of engineers and computer scientists, Vol. 2, No. 1, pp. 234-520,2009. [9] Vinod J Thomas, Diljo Thomas, “A Motion based Sign Language Recognition Method”, International Journal of Engineering Technology vol 3 Issue 4, ISSN 2349-4476, Apr 2015.
[10] Zhengmao, Z., Prashan, R., Monaragala, N., Malin, P. “Dynamic hand gesture recognition system using moment invariants”, IEEE Transactions on neural networking and computing, Vol. 21, No. 1, pp. 1034-1320, 2010
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