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2-D Speech Enhancement based on Curvelet Transform using Different Window Functions
by
A. K. Verma,
A. R. Verma,
Manoj Kumar
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 81 - Number 13 |
| Year of Publication: 2013 |
| Authors: A. K. Verma, A. R. Verma, Manoj Kumar |
10.5120/14069-2276
|
A. K. Verma, A. R. Verma, Manoj Kumar . 2-D Speech Enhancement based on Curvelet Transform using Different Window Functions. International Journal of Computer Applications. 81, 13 ( November 2013), 1-4. DOI=10.5120/14069-2276
@article{
10.5120/14069-2276,
author = {
A. K. Verma,
A. R. Verma,
Manoj Kumar
},
title = { 2-D Speech Enhancement based on Curvelet Transform using Different Window Functions },
journal = {
International Journal of Computer Applications
},
issue_date = { November 2013 },
volume = { 81 },
number = { 13 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = {
1-4
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume81/number13/14069-2276/
},
doi = { 10.5120/14069-2276 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:55:56.489602+05:30
%A A. K. Verma
%A A. R. Verma
%A Manoj Kumar
%T 2-D Speech Enhancement based on Curvelet Transform using Different Window Functions
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 13
%P 1-4
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper, an improved method based on Curvelet Transform using different window functions is presented for the speech enhancement. The window function is used for pre-processing of speech signals. In this method, instead of using two-dimensional (2-D) discrete Fourier Transform, Curvelet transform is employed with spectral magnitude subtraction method.
References
- Virag, N. Single channel speech enhancement based on masking properties of the human auditory system, IEEE Trans on Speech and Audio Processing, 7, 126-137, (1999).
- Yang, L. , Shuangtian, L. DCT speech enhancement based on masking properties of human auditory System. Proc, Inst of Acoust, Chinese Acad of Scien, 450-453,(2010).
- Lei, S. F, Tung, Y. K. , Speech enhancement for nonstationary noises by wavelet packet transform and adaptive noise estimation, Proceedings of Int. Symposium on Intelligent Signal Processing and Communication Systems, 41-44 (2005).
- Jr, J. D. , Hansen, J. , Proakis, J. Discrete-Time Processing of Speech Signals, NY: IEEE Press, 2000.
- Levitt, H. Noise reduction in hearing aids: An overview, Journal of Rehabilitation Research and Development, 38(1), 111-121, (2001).
- Berouti, M. , Schwartz, R, Makhoul, J. Enhancement of speech corrupted by acoustic noise, Proc. IEEE Int. Conf. on Acoust. , Speech, Signal Procs. , (1979), 208-211.
- Boll, S. F. Suppression of acoustic noise in speech using spectral subtraction, IEEE Transaction Acoust. , Speech, Signal Processing, 27, 113-120, (1979).
- Soon, I. Y. , Koh, S. N. , Speech enhancement using 2D Fourier transform, IEEE Transactions on speech and audio processing , 11717-724 ,( 2003).
- Vaseghi, S. V. Advanced digital signal processing and noise reduction, Wiley, 2nd edition, 270-290, (2000).
- Ephraim, Y. , Malah, D. Speech enhancement using a minimum-mean square error short-time spectral amplitude estimator, Acoustics, Speech, and Signal Processing 32(6) 1109-1121, (1984).
- Paliwal, K. K. , Basu, A. A speech enhancement method based on Kalman filtering, in Proc. IEEE Int. Conf. Acoust. , Speech, Signal Processing, 177-180, (1987).
- Huang, J. , Zhao, Y. A DCT-based fast signal subspace technique for robust speech recognition, IEEE Trans, on Speech and Audio Proc, 8(6), 747-751, (2000).
- Ephraim, Y. "Statistical-Model-Based Speech Enhancement Systems," Proceeding of the IEEE, 80(10), 1526-1555, (1992).
- Scalart, P. , Filho, J. V. Speech enhancement based on a priori signal to noise estimation, in Proc. ICASSP, 2, 629–632, (1996).
- Makhoul, J. A Fast Cosine Transform in One and Two Dimensions, IEEE Trans on Acoust, Speech, and Signal Proce, assp-28, no. 1, 27-34, (1980).
- Mittal, U. , Phamdo, N. Signal/noise KLT based approach for enhancing speech degraded by colored noise, IEEE Trans. Speech Audio Processing, vol. 8,159–167, (2000).
- Jafer, E. , Mahdi, A. E. Wavelete-based Perceptual Speech Enhancement Using Adaptive Threshold Estimation, In eurospeech 569-572, (2003).
- Bahoura, M. , Rouat, J. Wavelet Speech Enhancement Based on the Teager Energy Operator. IEEE Sig. Proc. Letters, vol. 8, 10-12, (2001).
- Kaiser,J. F. , Schafer, R. W. , On the use of the IO-sinh window for spectrum analysis. IEEE Trans Acoustics Speech Signal Process 28:105–107, (1980).
- Saramaki, T. A class of window functions with nearly minimum sidelobe energy for designing fir filters. In: Proceedings of the IEEE international symposium circuits and systems, Portland, Ore, USA p. 359–62 (1989).
- K. Avci, A. Nacaroglu, A New Window Based on Exponential Function, IEEE Conference on Research in Microelectronics and Electronics, (2008) 69-72.
- A. Kumar, B. Kuldeep, Design of M-channel cosine modulated filter bank using modified Exponential window. Journal of the Franklin Institute 349, 1304–1315, (2012).
- C. Plapous, C. Marro and P. Scalart, Improved signal-to-noise ratio estimation for speech enhancement IEEE Transaction. Audio, Speech, And Language Processing, 14, (2006).
- Plapous, C. , Marro, C. , Scalart, P. , Mauuary, L. A two-step noise reduction technique, InProc. IEEE International conference. Acoustic. Speech, Signal Process. Montréal, QC, Canada, 1, (2004), 289–299.
- Walker, J. S. A Primer on Wavelets and Scientific Applications 1999.
Index Terms
Computer Science
Information Sciences
Keywords