A prior knowledge-based noise reduction method with dual microphones

In this paper, a noise reduction method with dual microphones, based on the prior knowledge, is proposed to reduce the residual noise especially in the period of target speech absence (TSA). First, two cases, i.e. target speech presence and target speech absence were modeled by Gaussian mixture model (GMM), respectively. Then, we calculated the frame-based target speech present probability (TSPP) using Bayesian classification. Finally, a mask filter was presented by modifying the gain function of the improved phase-error based filter (IPBF) method using TSPP. Simulation results show that the proposed method outperforms the reference methods and could reduce noise effectively, particularly in the period of TSA.