Log-spectral magnitude MMSE estimators under super-Gaussian densities
Richard Christian Hendriks, Richard R. Heusdens, Jesper Jensen · 2009
Despite the fact that histograms of speech DFT coefficients are super-Gaussian, not much attention has been paid to develop estimators under these super-Gaussian distributions in combi-nation with perceptual meaningful distortion measures. In this paper we present log-spectral magnitude MMSE estimators un-der super-Gaussian densities, resulting in an estimator that is perceptually more meaningful and in line with measured his-tograms of speech DFT coefficients. Compared to state-of-the-art reference methods, the presented estimator leads to an im-provement of the segmental SNR in the order of 0.5 dB up to 1 dB. Moreover, listening tests show that the proposed estima-tor leads to significant improvement for the presented estimator over state-of-the-art methods. Index Terms: speech enhancement, log-spectral magnitude MMSE, super-Gaussian