Noise Reduction Based on Robust Principal Component Analysis ⋆
نویسندگان
چکیده
In this paper, we present a new speech enhancement method based on robust principal component analysis. In the proposed method, noisy signal is transformed into time-frequency domain where background noise is assumed as a low-rank component and human speech is regarded as a sparse compone. An inexact augmented Lagrange multipliers algorithm is conducted for solving the noise and speech separation problem. Experimental results show the RPCA based speech enhancement method can steadily obtain higher noise suppression performance in noisy conditions, compared to many traditional methods.
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تاریخ انتشار 2014