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A Natural Human-Machine Interaction via an Efficient Speech Recognition System

Shachi Sharma, Krishna Kumar Sharma, Himanshu Arora Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication: 2012
© 2012 by IJAIS Journal
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  1. Shachi Sharma, Krishna Kumar Sharma and Himanshu Arora. Article: A Natural Human-Machine Interaction via an Efficient Speech Recognition System. International Journal of Applied Information Systems 4(9):31-37, December 2012. BibTeX

    	author = "Shachi Sharma and Krishna Kumar Sharma and Himanshu Arora",
    	title = "Article: A Natural Human-Machine Interaction via an Efficient Speech Recognition System",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 4,
    	number = 9,
    	pages = "31-37",
    	month = "December",
    	note = "Published by Foundation of Computer Science, New York, USA"


This paper is motivated from non-technical users' problems in using technical interfaces of computer. In village areas, farmers face problems in using conventional ways to use computers, so in order to design a natural interaction way of human with computer, an efficient speech recognition system should be developed. For this we designed a system application. User has to speak commands and the system performs according to commands. This is all tested in the mobile environment and with varying users. And from the results, conclusion has been derived that the hybrid feature set outperformed in the noisy environment as compared to individual feature set with their dynamic features. And the result was approximately 5% higher. When DHMM is implemented in the system, results increased.


  1. T. Fong, I. Nourbakhsh, K. Dautenhahn, "A survey of socially interactive robots, robotics and Autonomous Systems", ISBN 978-3-902613-13-4, Elsevier Publications Ltd. , vol. 42, pp. 143-166, 2003.
  2. M. A. Goodrich, A. Schultz, "Human Robot Interaction: A Survery," Foundations and Trends in Human-Computer Interaction, ISBN 978-1-60198-092-2, Goodrich's Publications Ltd. , vol. 1, pp. 203-275, 2007.
  3. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proceedings of the IEEE, Feb1989.
  4. N. Zheng, Xia Li, Houwei Cao, Tan Lee, P. C. Ching, "Deriving MFCC parameters from the dynamic spectrum for robust speech recognition", ISCLP'08. 6th International Symposium on Chinese Spoken Language Processing, 2008.
  5. Sorensen and M. Swanholm, Speech coding and recognition course notes, [http://www. itu. dk. /courses/TKG/E2002], last accessed February 15, 2006.
  6. A. A. M. Abushariah, T. S. Gunawan, O. O. Khalifa, "English Digits Speech Recognition System Based on Hidden Markov Models", International Conference on Computer and Communication Engineering (ICCCE 2010), May 2010.
  7. K. K. Lavania , S. Sharma, K. K. Sharma, "Reviewing Human-Machine Interaction through Speech Recognition approaches and Analyzing an approach for Designing an Efficient System", Proc. of Int. Journal of Computer Applications, January 2012. Vol 38, No. 3, pp. 466-677.


Speech Recognition system, DHMM, hybrid feature set