An improved SNR estimator for speech enhancement

In this paper, we propose an MMSE a priori SNR estimator for speech enhancement. This estimator has similar benefits to the well-known decision-directed approach, but does not require an ad-hoc weighting factor to balance the past a priori SNR and current ML SNR estimate with smoothing across frames. Performance is evaluated in terms of estimation error and segmental SNR using the standard logSTSA speech enhancement method. Experimental results show that, in contrast with the decision-directed estimator and ML estimator, the proposed SNR estimator can help enhancement algorithms preserve more weak speech information and efficiently suppress musical noise.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Yao Ren, Michael T. Johnson
• Keywords: ICASSP 2008, ML SNR Estimate, Priori Snr Estimator, Signal Processing, SNR Estimator