Detection of Sound and Direction of Arrival (DOA) To Assist Deaf And Dumb People By Converting Voice Data Into Text

Authors(4) :-C. Sathish Kumar, V. Kaviya, R. Gayathri, G. Vinitha

The less-expensive, neck band wearable system is designed to help persons with hearing ailments by sensing alert sounds and analyzing the direction of arrival (DOA). The neck band kit contains two sound sensors which detect left 180 degree and right 180 degree. The prototype is composed of android app that will be connected to hardware kit through Bluetooth. Each sensor is connected to one of the analog inputs of the microcomputer. The power of the sensor signals is analyzed to detect alert sounds. Upon the detection of an alert sound, the user is notified about the detection of alert sound and it get shown on LCD screen. The developed smart application of android phones which can be connected to Bluetooth (HC-05), used to convert the voice data into text data and vice-versa by enhancing. A low cost programmed nano controller is used at the receiver to receive and display messages in the LCD display. The time required to sense and analyze the direction of an alert sound is around 35 msec.

Authors and Affiliations

C. Sathish Kumar
Assistant Professor, Department of Biomedical Engineering, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
V. Kaviya
Student, Department of Biomedical Engineering, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
R. Gayathri
Student, Department of Biomedical Engineering, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India
G. Vinitha
Student, Department of Biomedical Engineering, Adhiyamaan College of Engineering (Autonomous), Dr. M. G. R. Nagar, Hosur, Tamil Nadu, India

Nano controller, HC-025 Bluetooth, Smart app

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Publication Details

Published in : Volume 5 | Issue 5 | March-April 2020
Date of Publication : 2020-03-05
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 113-116
Manuscript Number : EBHBM011
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

C. Sathish Kumar, V. Kaviya, R. Gayathri, G. Vinitha, " Detection of Sound and Direction of Arrival (DOA) To Assist Deaf And Dumb People By Converting Voice Data Into Text", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 5, Issue 5, pp.113-116, March-April-2020.
Journal URL : https://ijsrst.com/EBHBM011
Citation Detection and Elimination     |      | |
  • D. Nashat, A. Shoker, F. Al-Swat and R. Al-Ebailan, "AN ANDROID APPLICATION TO AID UNEDUCATED DEAF-DUMB PEOPLE", International Journal of Computer Science and Mobile Applications.
  • D. Halawani, "Arabic Sign Language Translation System On Mobile Devices", International Journal of Computer Science and Network Security.
  • N. Salleh, J. Jais, L. Mazalan, R. Ismail, S. Yussof, A. Ahmad, A. Anuar and D. Mohamad, Sign Language to Voice Recognition: Hand Detection Techniques for Vision-Based Approach. Current Developments in Technology-Assisted Education.
  • Q. Munib, et al, “American Sign language (ASL) recognition based onHough Transform and neural Networks”, Expert Systems with Applications, 2007.
  • P.S Rajan and G. Balakrishnan, “Real time Indian Sign language recognition system to aid deaf-dumb people”, IEEE 13th International Conference on Communication Technologies, 2011, pp 737-742.
  • J. Kim et.al, “Bi-channel sensor fusion for an automatic sign language recognition”, in the 8th IEEE International Conference on Automatic Face and Gesture Recognition, Amsterdam, 2008, pp 1-6.
  • T. Kuroda, et al, “Consumer price data glove for sign language recognition”, in the International conference on disability, Virtual Reality and Associated Technologies, Oxford, UK, 2004, pp 253-258.
  • " target="_blank"> BibTeX
    |
  • D. Nashat, A. Shoker, F. Al-Swat and R. Al-Ebailan, "AN ANDROID APPLICATION TO AID UNEDUCATED DEAF-DUMB PEOPLE", International Journal of Computer Science and Mobile Applications.
  • D. Halawani, "Arabic Sign Language Translation System On Mobile Devices", International Journal of Computer Science and Network Security.
  • N. Salleh, J. Jais, L. Mazalan, R. Ismail, S. Yussof, A. Ahmad, A. Anuar and D. Mohamad, Sign Language to Voice Recognition: Hand Detection Techniques for Vision-Based Approach. Current Developments in Technology-Assisted Education.
  • Q. Munib, et al, “American Sign language (ASL) recognition based onHough Transform and neural Networks”, Expert Systems with Applications, 2007.
  • P.S Rajan and G. Balakrishnan, “Real time Indian Sign language recognition system to aid deaf-dumb people”, IEEE 13th International Conference on Communication Technologies, 2011, pp 737-742.
  • J. Kim et.al, “Bi-channel sensor fusion for an automatic sign language recognition”, in the 8th IEEE International Conference on Automatic Face and Gesture Recognition, Amsterdam, 2008, pp 1-6.
  • T. Kuroda, et al, “Consumer price data glove for sign language recognition”, in the International conference on disability, Virtual Reality and Associated Technologies, Oxford, UK, 2004, pp 253-258.
  • " target="_blank">RIS
    |
  • D. Nashat, A. Shoker, F. Al-Swat and R. Al-Ebailan, "AN ANDROID APPLICATION TO AID UNEDUCATED DEAF-DUMB PEOPLE", International Journal of Computer Science and Mobile Applications.
  • D. Halawani, "Arabic Sign Language Translation System On Mobile Devices", International Journal of Computer Science and Network Security.
  • N. Salleh, J. Jais, L. Mazalan, R. Ismail, S. Yussof, A. Ahmad, A. Anuar and D. Mohamad, Sign Language to Voice Recognition: Hand Detection Techniques for Vision-Based Approach. Current Developments in Technology-Assisted Education.
  • Q. Munib, et al, “American Sign language (ASL) recognition based onHough Transform and neural Networks”, Expert Systems with Applications, 2007.
  • P.S Rajan and G. Balakrishnan, “Real time Indian Sign language recognition system to aid deaf-dumb people”, IEEE 13th International Conference on Communication Technologies, 2011, pp 737-742.
  • J. Kim et.al, “Bi-channel sensor fusion for an automatic sign language recognition”, in the 8th IEEE International Conference on Automatic Face and Gesture Recognition, Amsterdam, 2008, pp 1-6.
  • T. Kuroda, et al, “Consumer price data glove for sign language recognition”, in the International conference on disability, Virtual Reality and Associated Technologies, Oxford, UK, 2004, pp 253-258.
  • " target="_blank">CSV

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