i-manager Publications

A Sign Translation App to Convert to ASL to Auditory English Language

Ayaan Farooqui *, Aayush Hatekar **, Prateek Angadi ***, Khyaati Shrikant ****

*-**** Department of Computer Engineering, Thakur College of Engineering and Technology, Maharashtra, India.

Periodicity:January - June'2021
DOI : https://doi.org/10.26634/jmt.8.1.18433

Abstract

Sign language is an optical communication language used by the people with speech and hearing disabilities for communication in their day-to-day conversation. Sign Language Recognition (SLR) system, which is required to recognize sign languages, has been widely studied for the past few years. Several input sensors, gesture segmentation, feature extraction and classification methods were used for the study. To eliminate the barrier in the communication between abled and disabled people is the main aim of this paper. This paper proposes a method to translate ASL in real time by mobile camera such that it can serve as a conversation medium between normal and deaf/dumb people.

Keywords

Sign Language, Sign Language Recognition (SLR), American Sign Language (ASL).

How to Cite this Article?

Farooqui, A., Hatekar, A., Angadi, P., and Shrikant, K. (2021). A Sign Translation App to Convert to ASL to Auditory English Language. i-manager's Journal on Mobile Applications and Technologies, 8(1), 1-7. https://doi.org/10.26634/jmt.8.1.18433

References

[1]. Cao, Z., Hidalgo, G., Simon, T., Wei, S. E., & Sheikh, Y. (2019). OpenPose: Realtime Multi-person 2D Pose Estimation using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1), 172-186. https://doi.org/10.1109/TPAMI.2019.2929257

[2]. Koller, O., Zargaran, O., Ney, H., & Bowden, R. (2016). Deep sign: Hybrid CNN-HMM for Continuous Sign Language Recognition. In Proceedings of the British Machine Vision Conference, 1-12.

[3]. Maxwell, C. (1892). A Treatise on Electricity and Magnetism (3^rd ed). Oxford: Clarendon.

[4]. Parton, B. S. (2006). Sign Language Recognition and Translation: A Multidisciplined Approach from the Field of Artificial Intelligence. Journal of Deaf Studies and Deaf Education, 11(1), 94-101. https://doi.org/10.1093/deafed/ enj003

[5]. Rajaganapathy, S., Aravind, B., Keerthana, B., & Sivagami, M. (2015). Conversation of Sign Language to Speech with Human Gestures. Procedia Computer Science, 50, 10-15. https://doi.org/10.1016/j.procs.2015. 04.004

[6]. Sahoo, A. K., & Ravulakollu, K. K. (2014). Vision Based Indian Sign Language Character Recognition. Journal of Theoretical & Applied Information Technology, 67(3), 43(1), 172-186. https://doi.org/10.1109/TPAMI.2019.2929257

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.