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).

A new objective speech quality measure, Bark Coherence Function is presented. The Coherence Function was used for evaluating the non-linear distortion of low-to-medium rate speech coders. However, it is not well suited for quality estimation in modern speech transmission, especially, CDMA mobile communication system. In the proposed method, Coherence Function is newly defined in psycho-acoustic domain as the cognition module of perceptual speech quality measure and evaluates the perceptual non-linear distortion of mobile system. The experimental results showed that the proposed method has good performance over CDMA PCS and digital cellular system.