Speech enhancement for nonstationary noise environments

In this paper, we propose a robust speech enhancement algorithm for nonstationary noise environments, which comprises a multiband spectral subtraction (MBSS) speech estimator and a minima controlled recursive averaging (MCRA) noise estimation. A multiband approach is obtained by dividing the whole spectrum into multiple subbands and applying spectral subtraction independently in each band. The noise estimate exploit the observation that the noise signal typically has a nonuniform effect on the spectrum of speech and is given by averaging the past spectrum power value and using a time and frequency dependent smoothing factor that is calculated based on the speech presence probability in subbands. We test the performance of proposed algorithm in various nonstationary noise environments. The experiment results confirm the superiority of the MBSS and MCRA estimator. Outstanding speech enhancement is achieved, while avoiding the residual musical noise phenomena.