Microcontroller Based Speech to Text Translation System

##plugins.themes.bootstrap3.article.main##

  •   Victor Sorochi Uko

  •   Gachada Benard Dubukumah

  •   Ibrahim Kafayat Ayosubomi

Abstract

For the purpose of an effective communication, speech becomes a convenient conduit to convey messages as an important activity in human life. The need for better reception of voice messages between humans and the environment they interact with becomes a trend and an area of interest that needs to be studied for improvements. A speech to text translation system is an embedded based design that convert analogue signals particularly voice from an input into digital signals that a computer or any electronic device can understand and perform a required task or display the equivalent digital signal in text on a screen. Speech translation systems mitigates the bottlenecks to an efficient communication caused by other varieties of communication methods. Even though speech translation and recognition designs haven’t been well explored for electronic integration due to complexity and variation of sound signals from sources, this low cost, simple and portable project was incorporated to serve as a substratum and alternative in speech to text translation designs using microcontroller, in other to bridge the gaps in the world of human communications. This research paper addresses design methodology, limitations, recommendations and applications of the implemented speech to text translation system for improved communication reception.


Keywords: Android Application, Embedded Design, Speech, Speech Translation and Text

References

P. Das, K. Acharjee, P. Das and V. Prasad, “Voice recognition system: speech-to-text” Journal of applied and fundamental science vol. 1, pp. 191-195, November 2015.

P. Khilari, and V. J. Bhope, “A review on speech to text conversion methods” International journal of advanced research in computer engineering & technology, vol. 4, no. 7, pp. 3067-3072, July 2015

P. Padhye, and V. Chavan, and S. Mane M. “Speech recognition operation with efficient accuracy rate and factors affecting it” International journal of advanced research in computer and communication engineering, vol. 5, no. 9, pp. 767-782, September 2016.

S. Das, “Speech recognition technique: a review” International Journal of engineering research and applications, vol. 2, no. 3, pp. 2071-2087.

B. R. Reddy and E. Mahender, “Speech to text conversion using android plateform” International journal of engineering research and applications, vol. 3, no. 1, pp. 253-258.

G. B. Dubukumah, U. V. Sorochi and A. Salisu “Fire monitoring, prevention and control system for market Shops” Communications on applied electronics, vol. 7, no. 31, pp. 26-31.

Bluetooth Module HC-05. (n.d). Retrieved from https://www.electronicwings.com/sensors-modules/bluetooth-module-hc-05-

Introduction to MAX 232. (n.d). Retrieved from https://www.theengineeringprojects.com/2017/07/introduction-to-max232.html

About RS 232. (n.d). Retrieved from https://en.wikipedia.org/wiki/RS-232.

Downloads

Download data is not yet available.

##plugins.themes.bootstrap3.article.details##

How to Cite
[1]
Uko, V., Dubukumah, G. and Ayosubomi, I. 2019. Microcontroller Based Speech to Text Translation System. European Journal of Engineering and Technology Research. 4, 12 (Dec. 2019), 149-154. DOI:https://doi.org/10.24018/ejers.2019.4.12.1697.