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This paper introduces a novel speech enhancement method based on Empirical Mode Decomposition (EMD) and soft-thresholding algorithms. A modified soft thresholding strategy is adapted to the intrinsic mode functions (IMF) of the noisy speech. Due to the characteristics of EMD, each obtained IMF of the noisy signal will have different noise and speech energy distribution, thus will have a different noise variance. Based on this specific noise variance, by applying the proposed thresholding algorithm to each IMF separately, it is possible to effectively extract the existing noise components. The experimental results suggest that the proposed method is significantly more effective in removing the noise components from the noisy speech signal compared to recently reported techniques. The significantly better SNR improvement and the speech quality prove the superiority of the proposed algorithm.