Abstract / truncated to 115 words (read the full abstract)

This thesis deals with minimum mean square error (MMSE) speech enhancement schemes in the short-time Fourier transform (STFT) domain with a focus on statistical models for speech and corresponding estimators. MMSE speech enhancement approaches taking speech presence uncertainty (SPU) into account usually consist of a common MMSE estimator for speech and an a posteriori speech presence probability (SPP) estimator. It is shown that both estimators should be based on the same statistical speech model, as they are in the same estimation framework and assume the same a priori knowledge. In order to give a synopsis of consistent MMSE estimation under SPU, typical common MMSE estimators and a posteriori SPP estimators are recapitulated. Furthermore, a new ... toggle 4 keywords

speech enhancement noise reduction mmse estimation statistical modeling


Fodor, Bal√°zs
Technische Universität Braunschweig
Publication Year
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May 10, 2015

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