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Reseach Article

An Efficient Approach to Keystroke Saving for the Blinds

by Bharat Kapse, Urmila Shrawankar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 17
Year of Publication: 2013
Authors: Bharat Kapse, Urmila Shrawankar
10.5120/13615-1386

Bharat Kapse, Urmila Shrawankar . An Efficient Approach to Keystroke Saving for the Blinds. International Journal of Computer Applications. 77, 17 ( September 2013), 19-27. DOI=10.5120/13615-1386

@article{ 10.5120/13615-1386,
author = { Bharat Kapse, Urmila Shrawankar },
title = { An Efficient Approach to Keystroke Saving for the Blinds },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 17 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 19-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number17/13615-1386/ },
doi = { 10.5120/13615-1386 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:50:17.984846+05:30
%A Bharat Kapse
%A Urmila Shrawankar
%T An Efficient Approach to Keystroke Saving for the Blinds
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 17
%P 19-27
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Today many computer applications are available for the Blinds to interact with computer systems. Although computer interaction through keyboard is time consuming for visually impaired, their efforts can be minimized. Keystroke minimization or Keystroke saving is one of the approaches in minimizing the efforts of Blinds. The paper describes the work to achieve Keystroke saving. As the word prediction requires large database, in this work set of domain specific databases are constructed, where each domain database contains thousands of most commonly used words of that domain. It also construct prefix tree dynamically by modifying the Trie data structure. This dynamic prefix tree structure is used to perform prefix matching. The prefix matching is then analyzed to predict the required words from several domain specific databases used in this work. The paper describes the implementation and working of prefix matching and word prediction. The work presented in the paper is particularly useful for the blinds, as the work has considered all the difficulties of Blinds in interaction to computer through keyboard. The results of word prediction using modified trie are improved than trie based implementation.

References
  1. Guerreiro, T. , Lagoa, P. , Nicolau, H. , Goncalves, D. , and Jorge,J. A. , "From Tapping to Touching: Making Touch Screens Accessible to Blind Users", IEEE Multimedia, pp. 48-50,October 2008.
  2. Ramiro Vel´azquez, Hermes Hern´andez, and Enrique Preza, "A Portable eBook Reader for the Blind", 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010.
  3. Pradeep Manohar, Aparajit Parthasarathy, "An Innovative Braille System Keyboard for the Visually Impaired",11th International Conference on Computer Modelling and Simulation,UKSim 2009.
  4. Bergroth, Lasse ; Hakonen, Harri ; Raita, Timo,"A survey of longest common subsequence algorithms", Seventh International Symposium on String Processing and Information Retrieval, SPIRE 2000.
  5. Coutinho, Luis Rodolfo Reboucas Girao, Anaxagoras Maia, Frota, Joao Batista Bezerra; Silva Jr. , Elias Teodoro, "Device to documents", 2012 Brazilian Symposium on Computing System Engineering.
  6. Shirbahadurkar, S. D. ; Bormane, Dattatraya S. ; Kazi, R. L, "Subjective and Spectrogram Analysis of Speech Synrhesisizer for Marathi TTS Using Concatenative Synthesis", 2010 International Conference on Recent Trends in Information, Telecommunication and Computing (ITC).
  7. Robert Sedgewick and Kevin Wayne, "Algorithms 4th edition" , 2012.
  8. Y. -H. E. Yang and V. K. Prasanna, "Memory-efficient pipelined architecture for large-scale string matching", In FCCM, 2009, pages 104 –111, april 2009.
  9. V. Srinivasan and G. Varghese, "Fast address lookups using controlled prefix expansion", ACM Trans. Comput. Syst. , 17:1–40,1999.
  10. Hoang Le, Viktor K. Prasanna, "A Memory-Efficient and Modular Approach for Large-Scale String Pattern Matching," IEEE Transactions on Computers, vol. 62, no. 5, pp. 844-857, May 2013
  11. Nasser Yazdani, Hossein Mohammadi, "DMP-tree: A dynamic M-way prefix tree data structure for strings matching", Advances in Computing Systems Science and Engineering, Volume 36, Issue 5, September 2010, Pages 818–834.
  12. Bayer R, McCreight C, "Organization and maintenance of large ordered indexes", Acta Inform 1972;1(3):173–89.
  13. Yazdani Nasser, Min Paul S, "Fast and salable schemes for IP lookup problem", in: Proceedings of the IEEE conference high performance switching and routing, Heidelberg Germany; 2000.
  14. Black, Paul E, ""Trie" , Dictionary of Algorithms and Data Structures", National Institute of Standards and Technology, Archived from the original on 2010-05-19.
  15. Yazdani Nasser, Min Paul S. "Prefix trees: new efficient data structures for matching strings of different lengths", In Proceedings of the IEEE database engineering conference (IDEAS 01). Grenoble, France; July 2001.
  16. R ramakrishnan and J. Gehrke , "Database Management Systems",3ed,2009.
  17. Urmila Shrawankar, Bharat Kapse, " Prefix Matching for Keystroke Minimization using B+ Tree", IEEE 8th International Conference on Computer Science & Education. Colombo, Sri Lanka, April 2013.
  18. Bharat Kapse, Urmila Shrawankar, " Word Prediction using B+ Tree for Braille Users", IEEE 2nd SCES, Allahabad, India, April 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Keystroke saving Word prediction prefix matching Trie Domain database