International Journal of Speech Technology

, Volume 18, Issue 2, pp 157–166 | Cite as

A wavelet based method for removal of highly non-stationary noises from single-channel hindi speech patterns of low input SNR

  • Sachin Singh
  • Manoj Tripathy
  • R. S. Anand


This paper presents a binary mask thresholding function in Doubachies10 wavelet transform for enhancement of highly non-stationary noise mixed single-channel Hindi speech patterns of low (negative) SNR. In the wavelet transform, a five level of decomposition is used and detailed coefficients of all five levels are given to binary mask thresholding function for removing noise and enhancing the speech patterns. The robustness of the proposed method is compared with the wildly popular methods such as log-mmse, test-psc, Wiener, IdBM, and spectral-subtraction on the basis of performance measure parameters viz SNR, PSNR, PESQ, and Cepstrum distance. The algorithms were implemented in MATLAB 7.1.


Speech enhancement Hindi speech patterns SNR  PESQ Cepstrum distance Wavelet transform 


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Electrical EngineeringIndian Institute of Technology RoorkeeRoorkeeIndia

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