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Most speech enhancement algorithms heavily depend on the noise power spectral density (PSD). Because this quantity is unknown in practice, estimation from the noisy data is necessary. We present a low complexity method for noise PSD estimation. The algorithm is based on a minimum mean-squared error estimator of the noise magnitude-squared DFT coefficients. Compared to minimum statistics based noise...
A novel multi-microphone speech enhancement method with low computational complexity using the generalized sidelobe canceller (GSC) structure based on LMS (least mean square) algorithm is proposed under stationary noise condition. In adaptive module of the presented method, speech signals in one frame share the same weight and update simultaneously instead of calculating weights respectively. Experimental...
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