Software Requirement Specification Using Reverse Speech Technology

International Journal of Computer Trends and Technology (IJCTT)          
© - November Issue 2013 by IJCTT Journal
Volume-5 Issue-4                           
Year of Publication : 2013
Authors :Santhy Viswam , Sajeer Karattil


Santhy Viswam , Sajeer Karattil"Software Requirement Specification Using Reverse Speech Technology"International Journal of Computer Trends and Technology (IJCTT),V5(4):170-174 November Issue 2013 .ISSN Published by Seventh Sense Research Group.

Abstract:- Speech analysis had been taken to a new level with the discovery of Reverse Speech (RS). RS is the discovery of hidden messages, referred as reversals, in normal speech. Works are in progress for exploiting the relevance of RS in different real world applications such as investigation, medical field etc. In this paper we represent an innovative method for preparing a reliable Software Requirement Specification (SRS) document with the help of reverse speech. As SRS act as the backbone for the successful completion of any project, a reliable method is needed to overcome the inconsistencies. Using RS such a reliable method for SRS documentation was developed.


[1] David John Oates, Reverse Speech: A New Theory about Lamguage,, Noarlunga Centre, Australia, 2008.
[2] David John Oates, It’s Only a Metaphor,, Noarlunga Centre, Australia, 1996.
[3] David John Oates, Reverse Speech: Voices From The Unconsciousness,, Noarlunga Centre, Australia, 1995.
[4] (2001) The Reverse Speech website. [Online]. Available:
[5] L. R. Rabiner and R. W. Schafer, Introduction to Digital Signal Processing, Foundations and Trends in Signal Processing, now Publishers Inc., 222 Rosewood Drive, Danvers, MA 01923, vol. 1, no 1–2, pp 1–194, 2007.
[6] J. Benesty, J. Chen, Y. Huang and I. Cohen, Noise Reduction in Speech Processing, Spriger topics in signal processing. Springer-Verlag Berlin Heidelberg, Germany, 2009, vol. 2.
[7] Sid-Ahmed Selouani, Speech Processing and Soft Computing, SpringerBriefs in Electrical and Computer Engineering. Springer Science+Business Media, LLC, New York, USA, 2011.
[8] Wei HAN, Cheong-Fat CHAN, Chiu-Sing CHOY and Kong-Pang PUN. “An Efficient MFCC Extraction Method in Speech Recognition”, Circuits and Systems, 2006.ISCAS 2006. Proceedings. 2006 IEEE International Symposium on, vol., pp.4 pp., 21-24 May 2006.
[9] K. U. Shajeesh, “Noise Cancellation Method for Robust Speech Recognition,” M. Eng. thesis, Amrita Vishwa Vidyapeetham, Ettimadai, Coimbatore, India, May 2012.
[10] Xiaodong Cui, Jing Huang, and Jen-Tzung Chien. “Multi-view and multi-objective semi-supervised learning for hmm-based automatic speech recognition”. Audio, Speech, and Language Processing, IEEE Transactions on, 20(7):1923 -1935, Sept. 2012.
[11] Li Deng, Xiao Li. Machine Learning Paradigms for Speech Recognition: An Overview. Audio, Speech, and Language Processing, IEEE Transactions on, 21(5):1060-1089, may 2013.
[12] Jonathan Kola, Carol Espy-Wilson and Tarun Pruthi, Voice Activity Detection. 2011.
[13] Chadawan Ittichaichareon, Siwat Suksri and Thaweesak Yingthawornsuk, “Speech recognition using mfcc extraction method in speech recognition,” in International Conference on Computer Graphics, Simulation and Modeling (ICGSM`2012), July 28-29, 2012 Pattaya pages 4 pp.-.
[14] Spectral Subtraction Basics. [Online]. Available: m

Keywords :— Reverse Speech, Software Requirement Specification (SRS), Speech Enhancement, Speech Recognition.