Smart Finger Gesture Recognition System for Silent Speakers

Authors

  • Gayathri. R  Assistant Professor (Sr. Gr.), Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India
  • Dr. K. Sheela Sobana Rani  Assistant Professor (Sr. Gr.), Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India
  • R. Lavanya  Associate Professor, Department of Electrical and Electronics Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India

DOI:

https://doi.org//10.32628/CSEIT195418

Keywords:

Flex Sensor, Raspbian, Espeak, Gesture Recoginition.

Abstract

Silent speakers face a lot of problems when it comes to communicate their thoughts and views. Furthermore, only few people know the sign language of these silent speakers. They tend to feel awkward to take part any exercises with the typical individuals. They require gesture based communication mediators for their interchanges. The solution to this problem is to provide them a better way to take their message across, “Smart Finger Gesture Recognition System for Silent Speakers” which has been proposed. Instead of using sign language, gesture recognition is done with the help of finger movements. The system consists of data glove, flex sensors, raspberry pi. The flex sensors are fitted on the data gloves and it is used to recognize the finger gestures. Then the ADC module is used to convert the analog values into digital form. After signal conversion, the value is given to Raspberry Pi 3, and it converts the signals into audio output as well as text format using software tool. The proposed framework limits correspondence boundary between moronic individuals and ordinary individuals. Therefore, the recognized finger gestures are conveyed into speech and text so that the normal people can easily communicate with dumb people.

References

  1. Abhijith Bhaskaran K, Anoop G Nair, Deepak Ram K, Krishnan Ananthanarayanan, H R Nandi Vardhan, (2016) “Smart Gloves for Hand Gesture Recognition”, International Conference on Robotics and automation for Humanitarian Applications (RAHA), pp.1-6.
  2. Anagha J.Jadhav and Mandar P.Joshi, (2016)“AVR Based Embedded System for Speech Impaired People”, International Conference on Automatic Control and Dynamic optimization techniques (ICACDOT), pp. 844-848.
  3. Ashish S.Nikam and Aarti G.Ambekar, (2016)“Sign Language Recognition using Image Based Hand Gesture Recognition Techniques”, Online International Conference on Green Engineering and Technologies (IC-GET), pp. 1-5.
  4. A.Batool, S.Rauf, T.Zia,T.Siddiqui, J.A.Shamsi, T.Q.Syed and A.U.Khan, (2014) “Facilitating Gesture-Based Actions for a Smart Home Concept”, International Conference on Open Source Systems and Technologies, pp. 6-12.
  5. Dhananjai Bajpai, Uddaish Porov, Gaurav Srivastav and Nitin Sachan, (2015) “Two Way Wireless Data Communication and American Sign Language Translator Glove for Images Text and Speech Display on Mobile Phone”, 5th International Conference on Communication Systems and Network Technologies, pp. 578-585.
  6. Emad E.Abdallah and Ebaa Fayyoumi, (2016) “Assistive Technology for Deaf People Based on Android Platform”, Procedia Computer Science, vol. 94, pp. 295-301.
  7. Fernando Ramirez-Garibay, Ceasar Millan Olivarria, Alejandro Ferderico Eufracio Aguilera and Joel C.Huegel, (2014) “My Vox-Device for the Communication between People: Blind, Deaf, Deaf-Blind and Unimpaired”, IEEE Global Humanitarian Technology Conference (GHTC), pp. 506-509.
  8. Geethu G Nath and Arun C S, (2017)“Real Time Sign Language Interpreter”, IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE), pp. 1-5.
  9. Harini Sekar, R.Rajashekar, Gosakan Srinivasan, Priyanka Suresh and Vineeth Vijayaraghavan, (2015)“Low-cost Intelligent Static Gesture Recognition System”, Annual IEEE System Conference (SysCon), pp. 1-6.
  10. Julien Marot and Salah Bourennane, (2017) “Raspberry Pi for Image Processing Education”, 25th European Signal Processing Conference (EUSIPCO), pp. 2364-2366.
  11. Kumud Tripathi, Neha Baranwal and G.C.Nandi, (2015) “Continuos Indian Sign Language Gesture Recognition and Sentence Formation”, Procedia Computer Science, vol. 54, pp. 523-531.
  12. B.G.Lee and S.M.Lee, (2017) “Smart Wearable Hand Device for Sign Language Interpretation System with Sensors Fusion”, IEEE Sensors Journal, vol. 18, Issue 3, pp. 1224-1232.
  13. Li Lei and Que Dashun, (2015) “Design of Data Glove and Chinese Sign Language Recognition System Based on ARM9”, 12th IEEE International Conference on Electronic Measurement and Instrument (ICEMI), vol. 03, pp. 1130-1134.
  14. Monique Bernice H.Flores, Charles Mholen B.Siloy, Carlos Oppus and Luisito Agustin, (2014) “User-Oriented Finger-Gesture Glove Controller with Hand Movement Virtualization Using Flex Sensors and a Digital Accelerometer”, International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), PP. 1-4.
  15. Neela Harish, S.Poonguzhali, (2015)“Design and Development of Hand Gesture Recognition System for Speech Impaired People”, International Conference on Industrial Instrumentation and Control (ICIC), pp. 1129-1133.
  16. Rishikanth C, Harini Sekar, Gautham Rajagopal, Ramesh Rajesh and Vineeth Vijayaraghavan, (2014)“Low Cost Intelligent Gesture Recognition Engine for Audio-Vocally Impaired Individuals”, IEEE Global Humanitarian Technology Conference (GHTC), pp. 628-634.
  17. Shreyashi Narayan Sawant and M.S.Kumbhar, (2014) “Real Time Sign Language Recognition using PCA”, IEEE International Conference on Advanced Communications, Control and Computing Technologies, pp. 1412-1415.
  18. Subhankar Chattoraj and Karan Vishwakarma, (2017) “Assistive System for Physically Disabled People using Gesture Recognition”, IEEE 2nd International Conference on Signal and Image Processing (ICSIP), pp. 60-65.
  19. Suraksha Devi and Suman Deb, (2017) “Low Cost Tangible Glove for Translating Sign Gestures to Speech and Text in Hindi Language”, 3rd International Conference on Computational Intelligence and Communication Technology (CICT), pp. 1-5.
  20. Vikas Kumawat, Shubham Jain, Vikram Vashisth, Neha Mittal and Bhupendra Kumar Jangir, (2017)“Design of Controlling Home Appliances Remotely Using Raspberry Pi”, 2nd International Conference for Convergence in Technology (I2CT), pp. 841-845.

Downloads

Published

2019-08-30

Issue

Section

Research Articles

How to Cite

[1]
Gayathri. R, Dr. K. Sheela Sobana Rani, R. Lavanya, " Smart Finger Gesture Recognition System for Silent Speakers, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 4, pp.238-250, July-August-2019. Available at doi : https://doi.org/10.32628/CSEIT195418