Toolbox for log-spectral magnitude MMSE estimators under super-Gaussian densities.
The toolbox can also be downloaded from: http://ict.ewi.tudelft.nl/~richard/log_spec_super_gaussV1.rar
The matlab files enclosed in this toolbox can be used to tabulate gain functions for log-spectral magnitude MMSE estimators under an assumed Generalized-Gamma model for the clean speech magnitude DFT coefficients.
For the theory behind these estimators and constraints on the parameters we refer to the article
 R. C. Hendriks, R. Heusdens and J. Jensen, "Log-Spectral Magnitude MMSE Estimators under Super-Gaussian Densities", Interspeech, pp. 1319 - 1322, 2009.
Short description of the 2 main m-files (see the headers of the files for more info):
For an assumed Generalized-Gamma prior density of the magnitude DFT coefficients with gamma=2 and specific
nu parameter the m-file
tabulates the gain function for the log-spectral magnitude DFT coefficients.
For mathematical expressions of the gain functions for these estimators see .
The range of a priori and a posteriori SNRs is -40 to 40 dB in 1 dB steps. Each row of the gain matrices is for a different a priori SNR, while a posteriori SNR varies along columns.
Given the tabulated gain function, a vector of gain values for pairs of a priori and a posteriori SNRs can be selected using the m-file
where a_post and a_priori are vectors with the a posteriori and a priori SNRs respectively.
The vectors a_post and a_priori should have equal lengths. The parameters a_post_range and a_priori_range indicate the ranges in dBs used in the gain table G.
The scriptfile log_mmse_supergaus gives an example of the usage of the aforementioned m-files.
Implementations of the special functions are based on
S. Zhang & J. Jin "Computation of Special Functions" (Wiley, 1996) with implementations available online: http://iris-lee3.ece.uiuc.edu/~jjin/routines/routines.html
The implementations of these special functions in the toolbox have been adapted with respect to the original implementations such that they can handle vector arguments as well.
Copyright 2009: Delft University of Technology, Information and Communication Theory Group. The software is free for non-commercial use.
This program comes WITHOUT ANY WARRANTY.
R. C. Hendriks
Richard Hendriks (2021). Toolbox for log-spectral magnitude MMSE estimators under super-Gaussian densities (https://www.mathworks.com/matlabcentral/fileexchange/25431-toolbox-for-log-spectral-magnitude-mmse-estimators-under-super-gaussian-densities), MATLAB Central File Exchange. Retrieved .
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