Noise Tracking Algorithm for Speech Enhancement

In this paper, the improved noise tracking algorithm for speech enhancement is proposed. This method is used to detect the speech presence probability based on chi square distribution. During speech presence period, the time varying smoothing factor is adjusted. In addition, the estimated noise variance is recursively smoothed then averaged for various noises. This proposed method can track the noise signal with different input SNR (0dB and 5dB) levels. The performance of the proposed and the existing methods are evaluated by various noise conditions. From these evaluated results, it is observed that the proposed method reduces the performance measures as 6% - 58% of MSE and 3% - 97% of LogErr as compared to that of the various existing algorithms under various noise conditions with optimal smoothing factors ap = 0.97 and ad = 0.7. When this is integrated into the speech enhancement, it improves the speech signal quality and intelligibility with less speech distortion and residual noise