Abstract
It is well known that the non-stationary noise is the most difficult to be removed in speech enhancement. In this paper a novel speech enhancement algorithm based on the empirical mode decomposition (EMD) and then ICA is proposed to suppress the non-stationary noise. The noisy speech is decomposed into components by the EMD and ICA-based vector space, and the components are processed and reconstructed, respectively, by distinguishing between voiced speech and unvoiced speech. There are no requirements of noise whitening and SNR pre-calculating. Experiments show that the proposed method performs well suppressing of the non-stationary noise in short-wave channel for speech enhancement.
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© 2006 Springer-Verlag Berlin Heidelberg
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Shen, LR., Li, XY., Yin, QB., Wang, HQ. (2006). Speech Enhancement in Short-Wave Channel Based on ICA in Empirical Mode Decomposition Domain. In: Rosca, J., Erdogmus, D., PrÃncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_88
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DOI: https://doi.org/10.1007/11679363_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
Online ISBN: 978-3-540-32631-1
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