Virtual talk assistance for Dumb and Deaf

Authors

  • Suchethana H C  Assistant Professor, ISE Department, JNNCE, Shivamogga, Karnataka, India
  • Arun Kumar P  Assistant Professor, ISE Department, JNNCE, Shivamogga, Karnataka, India

DOI:

https://doi.org//10.32628/IJSRSET122936

Keywords:

Speech To Text, Text To Speech technique, deaf and dumb community

Abstract

For the Deaf and Dumb community, the use of Information and Communication Technology has increased the ease of life for them. Deaf and dumb people communicate with help of sign language to pass their messages to each other. In this way, they can’t express their ideas the exact way, they want. The implementation of Speech To Text and Text To Speech technique for deaf and dumb people to make them communicate better. Here the compared elaborated research work done in the same field which may be helpful in identifying the drawbacks as well as methods to improvise the present technology. It presents a detailed methodology used in numerous research work and advancements for the deaf and dumb community.

References

  1. P. Pujol, S. Pol, C. Nadeu, A. Hagen, and H. Bourlard, "Comparison and combination of features in a hybrid HMM/MLP and a HMM/GMM speech recognition system," IEEE Transactions on Speech andAudio processing, 2005 vol. 13, pp. 14-22,.
  2. E. Zarrouk, Y. B. Ayed, and F. Gargouri, "Hybrid continuous speech recognition systems by HMM, MLP and SVM: a comparative study," International Journal of Speech Technology, vol. 17, pp. 223- 233, 2014.
  3. M. L. Seltzer, D. Yu, and Y. Wang, "An investigation of deep neural networks for noise robust speech recognition," in proceedings of IEEE International Conference on, 2013, pp. 7398-7402.
  4. O. Abdel-Hamid, L. Deng, and D. Yu, "Exploring convolutional neural network structures and optimization techniques for speech recognition," In Proceeding of IEEE paper Interspeech, 2013, pp. 3366- 3370.
  5. Y. Zheng, "Acoustic modeling and feature selection for speech recognition," In Proceeding of IEEE, 2005, pp.345-350.
  6. Deepa V.Jose, Alfateh Mustafa, Sharan R,”A Novel Model for Speech to Text Conversion” International Refereed Journal of Engineering and Science (IRJES)ISSN (Online), Volume 3, Issue 1 2319-2327,2014
  7. Chen, Jingdong, Chrzanowski, Mike, Coates, Adam, Diamos, Greg, et al. Deep speech 2”End-to- end speechrecognition in English and mandarin”, arXiv preprint arXiv,6th edition, 2015.
  8. KyungHyun, and Bengio, Yoshua “ Empirical evaluation of gated re-current neural networks on sequencemodelling”, arXivpreprint arXiv,8th edition ,2014.
  9. Saadman Shahid Chowdury, Atiar Talukdar, Ashik Mahmud, Tanzilur Rahman”Domain specific Intelligent personal assistant with bilingual voice command processing”,In proceeding of IEEE conference, 2018,pp.117-121.
  10. Veton Kepuska and Gamal Bohota,”Next generation of virtual assistant (Microsoft Cortana, Apple Siri, Amazon Alexa and Google Home)”,In Proceeding of IEEE conference, 2018,pp.234-240.
  11. Laura BURbach, Patrick Halbach, Nils Plettenberg, Johannes Nakyama, Matrina Ziefle, Andre Calero Valdez”Ok google, Hey Siri, Alexa. Acceptance relevant of virtual voice assistants”,In Proceeding of International communication conference IEEE, 2019,pp.567-571.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2022-06-30

Issue

Volume 9, Issue 3, May-June-2022

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Suchethana H C, Arun Kumar P, " Virtual talk assistance for Dumb and Deaf, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 3, pp.96-105, May-June-2022. Available at doi : https://doi.org/10.32628/IJSRSET122936