Abstract
This project is a prototype of data glove which has ability to convert the movement of figure into visual display and audible sound of predefined language. I have seen many people who find it difficult to communicate with other due to language problem or due to problem in vocal chord. In a diverse country like INDIA where various types of mother tongues is spoken. People form one region of country when travelled to other region find it difficult to convey their message, which make it tedious to survive them in other region. So this data glove can convert the speaker language into the listener language which make it possible to easy communication between different language speaker. There is approximately 70 million people in world who are deaf and dumb. These people use sign language to communicate with each other. But the person with no disability in vocal chord does not learn sign language, this means that not everyone can understand sign language. So it will be a tedious task for deaf or dumb person to communicate with other person having no knowledge of sign language. This data glove can be used to replace code language which is used during war. A particular command can be converted into a gesture and the commanding officer have to make particular gesture using his hand and the command is displayed on the command receiving personnel. Data glove consists of flex sensor. In this prototype I have used 3 flex sensor which produce 8 output result. You can increase no of flex sensor up to 5 on one glove which can produce 32 output. The output produce by combination of flex sensor on data glove is in analog form which is feeded to ADC channel of Arduino microcontroller. Analog to digital converter of microcontroller convert the analog input into digital form. This digital pattern is compared with stored data and then according to comparing result a particular sentence or word is displayed on a 16 * 2 LCD and same word or sentence is played on an 8 O speaker. Speaker and LCD output is for dumb people communication while only LCD is only sufficient for deaf person. This model consists of SD card which make it possible for storing as much audio as required means there will be no limitation of memory.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Otiniano, R., Amara, C.: Finger spelling recognition from RGB-D information using kernel descriptor. IEEE Trans. Neural Syst. Rehabil. Eng. 28(8), 124–184 (2006)
Zhengmao, Z., Prashan, R., Monaragala, N., Malin, P.: Dynamic hand gesture recognition system using moment invariants. IEEE Trans. Neural Netw. Comput. 21(1), 1034–1320 (2010)
Preetham, C., Ramakrishnan, G., Kumar, S., Tamse, A., Krishnapura, N.: Hand talk-implementation of a gesture recognizing glove
Anetha, K., Rejina P.J.: Hand talk-a sign language recognition based on accelerometer and SEMG data
Ong, S.C.W., Ranganath, S.: Automatic sign language analysis: a survey and the future beyond lexical meaning. IEEE Trans. Pattern Anal. Mach. Intell. 27(6), 873–891 (2005)
Mayura, S.K., Prasad R.K.: Gesture controlled robotic hand using flex sensor. IJSRD—Int. J. Sci. Res. Dev. 3(7), 2321–0613 (2015) ISSN (online)
Saggio, G., Riillo, F., Sbernini, L., Quitadamo, L.R.: Resistive flex sensors: a survey. Smart Mat. Struct. 25(1), 013001 (2015)
Kekre, M., Vaishali, K.: Speaker identification by using vector quantization. IEEE Trans. Mechatronics 15(1), 1034–1620 (2010)
Elleuch, H., Wali, A., Samet, A. Alimi, A.M., 2015, December. A static hand gesture recognition system for real time mobile device monitoring. In: 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), IEEE, pp. 195–200 (December 2015)
Lopes, N.V., Pinto, F., Furtado, P. Silva, J.: IoT architecture proposal for disabled people. In 2014 IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), IEEE, pp. 152–158 (October 2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Kumar, V., Raghuwanshi, S.K., Kumar, A. (2020). Hand Talk System for Deaf and Dumb Person. In: Manna, S., Datta, B., Ahmad, S. (eds) Mathematical Modelling and Scientific Computing with Applications. ICMMSC 2018. Springer Proceedings in Mathematics & Statistics, vol 308. Springer, Singapore. https://doi.org/10.1007/978-981-15-1338-1_26
Download citation
DOI: https://doi.org/10.1007/978-981-15-1338-1_26
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1337-4
Online ISBN: 978-981-15-1338-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)