Radha H G, Shruti S D, Kanya B S


Communications between deaf-mute and a normal person have always been a challenging task.The paper describes a way to reduce this communication barrier by developing an assistive device  for deaf-mute persons. The system consists of a sign language translator, speech recognition unit, traffic sensing module and GSM-GPS unit. Sign language translator module  translates the gesture signs to text and further it is converted to voice . To convert acoustic speech to text form speech recognition system is used. Hence two way communication is possible.To  provide assistance at times of danger and critical situation GSM and GPS technologies are used that transmit the gestures to the respective guardian of deaf-mute person along with location and time information. Traffic alert is provided to deaf person using sound sensor, obstacle sensor and vibrator. The main advantage of this project is, it can be used as an assistive device for deaf-mute person for both communication purpose and safety purpose.


Sign language; speech recognition; flex sensors; glove; traffic alert; GSM; GPS;


Seong-Whan Lee, “Automatic Gesture Recognition for Intelligent Human-Robot Interaction” Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (FGR’06) ISBN # 0-7695-2503-2/06

. Md. Al-Amin Bhuiyan, “On Gesture Recognition for Human-Robot Symbiosis”, The 15th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN06), Hatfield, UK, September 6-8, 2006, pp.541-545

. SanshzarKettebekov, Mohammed Yeasin and Rajeev Sharma, “Improving Continuous Gesture Recognition with Spoken Prosody”, Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’03), ISBN # 1063-6919/03, pp.1-6

. Byung-Woo Min, Ho-Sub Yoon, Jung Soh, Yun-Mo Yangc, and ToskiakiEjima, “Hand Gesture Recognition Using Hidden Markov Models”, ISBN # 0-7803-4053-1/97, pp.4232-4235

. Andrew D. Wilson and Aaron F. Bobick, “Parametric Hidden Markov Models for Gesture Recognition”, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 21, NO. 9, SEPTEMBER 1999, pp. 884-900

. Toshiyuki Kirishima, Kosuke Sato and KunihiroChihara, “Real-Time Gesture Recognition by Learning and Selective Control of Visual Interest Points”, IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 27, NO. 3, MARCH 2005, pp. 351-364

. Attila Licsár and TamásSzirány, “Dynamic Training of Hand Gesture Recognition System”, Proceedings of the 17th International Conference on Pattern Recognition (ICPR’04), ISBN # 1051- 4651/04,

. Juan P. Wachs, Helman Stern and Yael Edan, “Cluster Labeling and Parameter Estimation for the Automated Setup of a Hand-Gesture Recognition System”, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems And Humans, VOL. 35, NO. 6, NOVEMBER 2005, pp. 932-944

. Hong Li and Michael Greenspan, “Multi-scale Gesture Recognition from Time-Varying Contours”, Proceedings of the Tenth IEEE International Conference on Computer V

Higgins, E.L., &Zvi, J.C. (1995). Assistive technology for postsecondary students with learning disabilities: From research to practice. Annals of Dyslexia, 45: 123-143.

Wetzel, K. (1996). Speech-recognizing computers: “A written communication tool for students with learning disabilities” Journal of Learning Disabilities, 29(4): 371-380.

Schreier, E.M.*, Levanthal, D.D., Uslan, M.M. (1991). Access technology for blind and visually impaired persons. Technology and Disability,1 (1), 19-23.

Raskind, Marshall H. and Higgin, Eleanor L. “Speaking to read: The effects of speech recognition technology on the reading and spelling performance of children with learning disabilities”Annals of Dyslexia, Volume. 49, Number 1/December 1999.

Sign Language to Speech Translation System Using PIC Microcontroller (Gunasekaran. K et al. / International Journal of Engineering and Technology (IJET) ISSN : 0975-4024 Vol 5 No 2 Apr-May 2013)

Multi-purpose embedded voice assistance gadget(International Journal of Electronics Signals and Systems (IJESS) ISSN: 2231- 5969, Vol-2, ISS-2,3,4, 2012

praveenkumar s havalagi, shruthiurfnivedita ”the amazing digital gloves that give voice to the voiceless” issn: 2231-1963, Mar. 2013.

shoaibahmed .v ” hand gesture recognition and voice conversion system for differentially able dumb people” 2012

Full Text: PDF


  • There are currently no refbacks.

Copyright © 2012 - 2018, All rights reserved.|

Creative Commons License
International Journal of Innovative Technology and Research is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJITR , Permissions beyond the scope of this license may be available at