Speech enhancement based on novel two-step a priori SNR estimators

A widely used method to determine the a priori SNR from noisy speech is the decision directed (DD) approach, but the a priori SNR follows the a posteriori SNR with a delay of one frame in speech frames. As a consequence, the performance of the noise reduction system degrades. In order to overcome this artifact, we propose three computationally simple and efficient two-step methods based on the minimum mean square error (MMSE), the maximum a posteriori (MAP) and the joint MAP criteria for the estimation of the a priori SNR for speech enhancement. The proposed methods avoid the delay problem while keeping the advantages of the DD method. The performance of the proposed a priori SNR estimation methods are evaluated and compared with the conventional DD method by extensive objective quality measures and yield better results than the DD approach-based speech enhancement system.