Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations
IEEE International Conference on Acoustics, Speech and Signal Processing, 2008: ICASSP; Las Vegas, NV, March 31, 2008 - April 4, 2008
1520-6149, 978-1-4244-1484-0, 978-1-4244-1483-3
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.
Ren, Yao and Johnson, Michael T., "An Improved SNR Estimator for Speech Enhancement" (2008). Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations. 18.