Abstract
Traditional singular value decomposition (SVD) based speech enhancement algorithms are usually limited by the use of a fixed order of retained singular values which may not be optimal for time-varying noise corrupted speech signals. In this chapter, we propose the use of a Frobenius-norm (F-norm) constrained truncated (FCTSVD) algorithm in an analysis-by-synthesis procedure for choosing the appropriate order of retained singular values for speech enhancement. It allows for self-adaptation in time and for different noise and noisy speech characteristics. Also, it leads to the best approximation of original speech in terms of SNR. The proposed algorithm has been tested and compared with a traditional SVD algorithm for different noise types and levels. Simulation results show that it achieves higher SNR improvements for both additive white noise and colored noise as compared to a traditional SVD algorithm.
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Chen, G., Ngee Koh, S., Yann Soon, I. (2005). Speech Enhancement Based on F-Norm Constrained Truncated SVD Algorithm. In: Abut, H., Hansen, J.H., Takeda, K. (eds) DSP for In-Vehicle and Mobile Systems. Springer, Boston, MA. https://doi.org/10.1007/0-387-22979-5_11
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DOI: https://doi.org/10.1007/0-387-22979-5_11
Publisher Name: Springer, Boston, MA
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