Improving the Performance of the Minimum Statistics Noise Estimator for Single Channel Speech Enhancement

This paper proposes an algorithm to improve the performance of the noise power spectrum estimation using the minimum statistics (MS). The minimum statistics noise estimator (MSNE) that is most efficient for speech enhancement often underestimates noise power when the signal characteristics changes abruptly. The proposed algorithm improves the accuracy of noise estimation by removing harmonic components of the speech signal. Simulation results verify that the performance of the proposed algorithm is better than that of the conventional algorithm in terms of the segmental SNR (SegSNR) and the spectral distance (SD).