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A New Approach for Speech Enhancement Based On Eigenvalue Spectral Subtraction
Jamal Ghasemi, Karami mollaei
Pages - 34 - 41     |    Revised - 30-09-2009     |    Published - 21-10-2009
Volume - 3   Issue - 4    |    Publication Date - August 2009  Table of Contents
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KEYWORDS
Eigenvalues, singular values decomposition, Spectral Subtraction, Speech enhancement
ABSTRACT
In this paper, a phase space reconstruction-based method is proposed for speech enhancement. The method embeds the noisy signal into a high dimensional reconstructed phase space and uses Spectral Subtraction idea. The advantages of the proposed method are fast performance, high SNR and good MOS. In order to evaluate the proposed method, ten signals of TIMIT database mixed with the white additive Gaussian noise and then the method was implemented. The efficiency of the proposed method was evaluated by using qualitative and quantitative criteria.
CITED BY (21)  
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8 Anoop, V., & Rao, P. V. (2013). Speech Signal Quality Improvement Using Cuckoo Search Algorithm. International Journal of Engineering Innovations and Research, 2(6), 519.
9 Ghasemi, J., Ghaderi, R., Mollaei, M. K., & Hojjatoleslami, S. A. (2013). A novel fuzzy Dempster–Shafer inference system for brain MRI segmentation. Information Sciences, 223, 205-220.
10 Ghasemi, J., Mollaei, M. R. K., Ghaderi, R., & Hojjatoleslami, A. (2013). Multi-Dimensional Fuzzy C-Mean Considering Spatial Information for Brain MRI Segmentation. Majlesi Journal of Electrical Engineering, 8(1), 37-44.
11 Ghasemi, J., Mollaei, M. R. K., Ghaderi, R., & Hojjatoleslami, A. (2012). Brain tissue segmentation based on spatial information fusion by Dempster-Shafer theory. Journal of Zhejiang University SCIENCE C, 13(7), 520-533.
12 Mohedden, S. K., Zia-Ur-Rahman, M., Krishna, K. M., & Rao, B. R. M. Battle Field Speech Enhancement using an Efficient Unbiased Adaptive Filtering Technique.
13 Ghasemi, J., Mollaei, M. R. K., Ghaderi, R., & Hojjatoleslami, A. (2011, November). Brain Tissue Segmentation by FCM and Dempster-Shafer Theory. In Machine Vision and Image Processing (MVIP), 2011 7th Iranian (pp. 1-5). IEEE.
14 Prameela, K., Kumar, M. A., Zia-Ur-Rahman, M., & Rao, B. R. M. (2011). Non Stationary Noise Removal from Speech Signals using Variable Step Size Strategy. International Journal of Computer Science & Communication Networks, 1(1).
15 Rahman, M. Z. U., Mohedden, S. K., Rao, B. R. M., Reddy, Y. J., & Karthik, G. V. S. (2011). Filtering Non-Stationary Noise in Speech Signals using Computationally Efficient Unbiased and Normalized Algorithm. International Journal on Computer Science and Engineering, ISSN, 0975-3397.
16 Karthik, G. V. S., Kumar, M. A., & Rahman, M. Z. U. (2011). Speech Enhancement Using Gradient Based Variable Step Size Adaptive Filtering Techniques. International Journal of Computer Science & Emerging Technologies (E-ISSN: 2044-6004), 2(1), 168-177.
17 Ghasemi, J., Mollaei, M. R. K., Ghaderi, R., & Hojjatoleslami, A. (2011, July). Separation of brain tissues in MRI based on multi-dimensional FCM and spatial information. In Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on (Vol. 1, pp. 247-251). IEEE.
18 Murthy, A. S. N., & Rani, D. E. (2011). Speech Enhancement by Cascaded Spectral Subtraction. Digital Signal Processing, 3(5), 188-191.
19 Afzalian, A., Mollaei, M. R. K., & Ghasemi, J. A Combined Voice Activity Detector Based On Singular Value Decomposition and Fourier Transform. Signal Processing: An International Journal (SPIJ), 4(1), 54.
20 Farsi, H. (2010). Improvement of minimum tracking in minimum statistics noise estimation method. Signal Processing: An International Journal (SPIJ), 4(1), 17.
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Dr. Jamal Ghasemi
- Iran
jghasemi@stu.nit.ac.ir
Mr. Karami mollaei
- Iran