Research Article

Hindi Speech Recognition System with Robust Front End-Back End Features

by  Atul Gairola, Swapna Baadkar
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Issue 1
Published: February 2013
Authors: Atul Gairola, Swapna Baadkar
10.5120/10601-5305
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Atul Gairola, Swapna Baadkar . Hindi Speech Recognition System with Robust Front End-Back End Features. International Journal of Computer Applications. 64, 1 (February 2013), 42-45. DOI=10.5120/10601-5305

                        @article{ 10.5120/10601-5305,
                        author  = { Atul Gairola,Swapna Baadkar },
                        title   = { Hindi Speech Recognition System with Robust Front End-Back End Features },
                        journal = { International Journal of Computer Applications },
                        year    = { 2013 },
                        volume  = { 64 },
                        number  = { 1 },
                        pages   = { 42-45 },
                        doi     = { 10.5120/10601-5305 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2013
                        %A Atul Gairola
                        %A Swapna Baadkar
                        %T Hindi Speech Recognition System with Robust Front End-Back End Features%T 
                        %J International Journal of Computer Applications
                        %V 64
                        %N 1
                        %P 42-45
                        %R 10.5120/10601-5305
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

The ideal aim of a speech recognition system is efficient and accurate conversion of speech signal into text message without any dependence on device, environment, and speaker. In this paper a system for Hindi speech recognition is discussed employing robust front end- back end techniques. At front end MF-PLP is used for feature extraction while continuous density HMM is used at the back end for evaluation. A comparison of MFCC, PLP & MF-PLP is also presented to show the robust characteristics of MF-PLP.

References
  • H. Hermansky, "Perceptually predictive (PLP) analysis of speech," Journal of Acoustic Society of America, vol. 87, 1990, pp. 1738-1752.
  • A. O. Afolabi, A. Williams, and O. Dotun, "Development of a text dependent speaker identification security system", Research Journal of Applied Sciences, 2 (6), pp. 677-684, 2007.
  • K. Samudravijaya, Barot & Maria, "A Comparison of Public-Domain Software Tools for Speech Recognition", In WSLP, pp. 125-131, 2003.
  • R. Josef and P. Pollak , "Modified Feature Extraction Methods in Robust Speech Recognition", Radioelektronika, 17th IEEE International Conference, pp. 1-4, (2007).
  • Andra´s Zolnay , Daniil Kocharov , Ralf Schlüter and Hermann Ney, "Using multiple acoustic feature sets for speech recognition", Science direct, Speech Communication 49 , pp. 514–525, 2007.
  • study on the effect of additive noise on automatic speech recognition system", Reports of NATO Research Study Group (RSG. 10), 1992.
  • N. Goel, S. Thomas, M. Agarwal et al. "Approaches to Automatic Lexicon Learning with Limited Training Examples", Proc. of IEEE Conference on Acoustic Speech and Signal Processing, 2010.
  • S. F. Boll, "Suppression of Acoustic Noise in Speech using Spectral Subtraction", IEEE Transaction of Acoustic, Speech and Signal Processing, Vol. 27, No. 2, 1979, pp. 113-120.
  • H. Hermansky and N. Morgan, "RASTA Processing of Speech", IEEE Transaction on Speech and Audio Processing, Vol. 2, No. 4, 1994, pp. 578-589.
  • S. Young, "A Review of Large Vocabulary Continuous Speech Recognition", IEEE Signal Processing Mag. , Vol. 13, 1996, pp. 45-57.
  • C. H. Lee, J. L. Gauvain, R. Pieraccini, and L. R. Rabiner, "Large Vocabulary Speech Recognition using Subword Units", Speech Communication, Vol. 13, 1993, pp. 263-279.
  • X. D. Huang, H. W. Hon, M. Y. Hwang, and K. F. Lee, "A comparative study of discrete, semi continuous and continuous hidden Markov models," Computer Speech and Language, vol. 7(4), 1993, pp. 359-368.
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Feature Extraction Front End Back End MFCC PLP MF-PLP CDHMM

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