Use of Machine Learning Applications for Speech Impaired People

  • Rajeshri Pravin Shinkar

Abstract

While sign language is very important to deaf-mute people to communicate both with normal people and with themselves; it is still getting little attention from the normal people. We, as normal people, tend to ignore the importance of sign language unless there are loved ones who are deaf-mute. One of the solutions to communicate with the deaf-mute people is by using the services of sign language interpreters. But the usage of sign language interpreters can be costly. A cheap alternative to replace the interpreters is the use of a model that can automatically translate their actions into words. This paper covers the development of such a model which helps to automatically detect our actions in real time using the Mediapipe model and translate the same into respective text format.

Keywords: Mediapipe, Gesture, sign language

Downloads

Download data is not yet available.

References

[1] Brill R. 1986. The conference of Educational Administrators Serving the Deaf: A History. Washington, DC: Gallaudet University Press.
[2] Banerji J. N. 1928. India International Reports of Schools for the Deaf. Washington City: Volta Bureau. Pp. 18-19
[3] Suryapriya A. K., Sumam S. and Idicula M 2009. Design and Development of a Frame based MT System for English to ISL. World congress on Nature and Biologically Inspired Computing. Pp 1382-1387.
Statistics
0 Views | 0 Downloads
How to Cite
Shinkar, R. P. (2023). Use of Machine Learning Applications for Speech Impaired People. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 9(1), 61-66. https://doi.org/10.33130/AJCT.2023v09i01.012