NDLI: MMSE and maximum a posteriori estimators for speech enhancement in additive noise assuming a t-location-scale clean speech prior

Content Provider	IET Digital Library
Author	Faraji, Neda Kohansal, Akram
Abstract	The authors derive closed form solutions for the minimum mean square error (MMSE) and maximum a posteriori estimators for speech enhancement in additive Gaussian noise assuming a t-location-scale probability density function (PDF) as clean speech prior. Fitting a t-location-scale PDF to the real and imaginary parts of the discrete fourier transform (DFT) coefficients of clean speech signals demonstrates the lower Jensen–Shannon divergence compared to the other heavy-tailed distributions such as Laplacian and gamma. The authors utilise the two presented estimators along with the Wiener filter and MMSE estimators based on Laplacian, gamma, and generalised gamma prior PDFs to enhance noisy signals from the NOIZEUS database. All the estimators are compared together in terms of both signal and noise distortions. The obtained results show that their proposed MMSE estimator results in the minimum squared error and signal distortion to estimate the complex-valued DFT coefficients of speech. The quality assessments of the enhanced signals are also performed in terms of perceptual evaluation of speech quality, segmental and general SNRs.
Starting Page	532
Ending Page	543
Page Count	12
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 4, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2017.0446
Journal	IET Signal Processing
Publisher Date	2018-01-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additive Gaussian Noise Clean Speech Signal Complex-valued DFT Coefficient Discrete Fourier Transform Filtering Method in Signal Processing Gamma Prior PDF Gaussian Noise General SNR Generalised Gamma Prior PDF Integral Transforms in Numerical Analysis Interpolation And Function Approximation Jensen-Shannon Divergence Estimator Laplacian Prior PDF Least Mean Squares Method Maximum Likelihood Estimation Maximum-a-posteriori Estimators Minimum Mean Square Error Minimum Squared Error MMSE Estimator Numerical Analysis Perceptual Evaluation Probability Segmental SNR Signal Distortion Speech And Audio Signal Processing Speech Enhancement Speech Processing Technique Speech Quality SNR Statistics T-location-scale Clean Speech Prior T-location-scale PDF T-location-scale Probability Density Function Wiener Filter
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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