A NMF-Based Speech Enhancement Method Using a Prior Time Varying Information and Gain Function 


Vol. 38,  No. 6, pp. 503-511, Jun.  2013


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  Abstract

This paper presents a speech enhancement method using non-negative matrix factorization. In training phase, we can obtain each basis matrix from speech and specific noise database. After training phase, the noisy signal is separated from the speech and noise estimate using basis matrix in enhancement phase. In order to improve the performance, we model the change of encoding matrix from training phase to enhancement phase using independent Gaussian distribution models, and then use the constraint of the objective function almost same as that of the above Gaussian models. Also, we perform a smoothing operation to the encoding matrix by taking into account previous value. Last, we apply the Log-Spectral Amplitude type algorithm as gain function.

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  Cite this article

[IEEE Style]

K. Kwon, Y. G. Jin, S. H. Bae, N. S. Kim, "A NMF-Based Speech Enhancement Method Using a Prior Time Varying Information and Gain Function," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 6, pp. 503-511, 2013. DOI: .

[ACM Style]

Kisoo Kwon, Yu Gwang Jin, Soo Hyun Bae, and Nam Soo Kim. 2013. A NMF-Based Speech Enhancement Method Using a Prior Time Varying Information and Gain Function. The Journal of Korean Institute of Communications and Information Sciences, 38, 6, (2013), 503-511. DOI: .

[KICS Style]

Kisoo Kwon, Yu Gwang Jin, Soo Hyun Bae, Nam Soo Kim, "A NMF-Based Speech Enhancement Method Using a Prior Time Varying Information and Gain Function," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 6, pp. 503-511, 6. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880