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Glove to Translate Sign Language

Bodke Sulakshana1 , Alai Gayatri2 , Shinde Dipali3 , Pawar Sonali4

Section:Review Paper, Product Type: Journal Paper
Volume-3 , Issue-9 , Page no. 178-180, Sep-2015

Online published on Oct 01, 2015

Copyright © Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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How to Cite this Paper

IEEE Style Citation: Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali, “Glove to Translate Sign Language,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.178-180, 2015.

MLA Style Citation: Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali "Glove to Translate Sign Language." International Journal of Computer Sciences and Engineering 3.9 (2015): 178-180.

APA Style Citation: Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali, (2015). Glove to Translate Sign Language. International Journal of Computer Sciences and Engineering, 3(9), 178-180.

BibTex Style Citation:
@article{Sulakshana_2015,
author = {Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali},
title = {Glove to Translate Sign Language},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2015},
volume = {3},
Issue = {9},
month = {9},
year = {2015},
issn = {2347-2693},
pages = {178-180},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=663},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=663
TI - Glove to Translate Sign Language
T2 - International Journal of Computer Sciences and Engineering
AU - Bodke Sulakshana, Alai Gayatri, Shinde Dipali, Pawar Sonali
PY - 2015
DA - 2015/10/01
PB - IJCSE, Indore, INDIA
SP - 178-180
IS - 9
VL - 3
SN - 2347-2693
ER -

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Abstract

This system describe talkable hand glove system which aims at translation of sign language to analyze text and voice. This system consists of a talk able glove that can be worn by a deaf/dumb person to facilitate the communication in real-time with other people. The system translates the hand finger motion to corresponding letters using IR sensors and a Microcontroller. Our main goal is to identify 26 alphabets and display text on the LCD. Once the text is obtained on the LCD then text to speech conversion operation is carried out and finally a voice output is obtained. Further, the text gain can also be viewed on a LCD or any portable hand held device. Our main aim is to set an interface between the Deaf or Dumb and normal people to improve the communication capabilities so that they can communicate handily with others. We mount IR sensor on the talk able hand glove and propose and efficient methodology to convert these sign languages. This system will simplify the communication of deaf or dumb people with people able to normal communications without the need of a human translator

Key-Words / Index Term

IR sensor,H12E encoder,H12D decoder,Transmitter,Receiver

References

[1]. Bhavina Patel, Vandana Shah, Ravindra Kshirsagar: ”Microcontroller Based Gesture Recognition System For The Handicap People”, JERS/Vol. II/ Issue IV/ 113-115/ October-December, 2011
[2]. Kuldeep Singh Rajput ,Shashank Deshpande,Uma Mudenagudi :“Interactive Accelerometric Glove For Hearing Impaired”, AIML Journal, vol. 7, 2013
[3]. Gourab Talukdar,Omkar Gondhalekar: “Hand Gesture Recognition System”, International Journal of Scientific and Research Publications, Volume 4, Issue 2,SSN 2250-3153,Feb 2014
[4]. Gunasekaran Manikandan : “Sign Language To Speech Translation System Using PIC Microcontroller”, International Journal of Engineering and Technology, ISSN : 0975-4024 Vol 5,No 2,Apr-May 2013.
[5]. Priyanka Lokhande , Riya Prajapati: “Data Gloves for Sign Language Recognition System”, International Journal of Computer Applications (0975 – 8887),March 2015
[6]. Gunasekaran. K1, Manikandan. R2: “ Sign Language to Speech Translation”,2014