Comparison and Signal-Component-Wise Instrumental Evaluation of MMSE Log-Spectral Amplitude Estimation Under Speech Presence Uncertainty
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Fodor, Balázs; Fingscheidt, Tim (Institute for Communications Technology, Technische Universität Braunschweig, 38106 Braunschweig, Germany)
This paper presents an overview of MMSE log-spectral amplitude (LSA) estimators under speech presence uncertainty (SPU). These are the nonlinear MMSE LSA estimator, the multiplicatively modified MMSE LSA estimator, and the optimally modified MMSE LSA estimator. It turns out that the instrumental evaluation of speech and noise signal components needs to be carried out for the nonlinear MMSE LSA estimator by a black-box approach, due to the nonlinear nature of the estimator. For a comparison, all other estimators were evaluated by that black-box approach as well. This is indeed not typical in speech enhancement, although there are further estimators not being a linear function of the noisy speech signal (amplitude). The black-box approach allows advantageously for a signal-component-wise instrumental evaluation of them, too. It is worthwhile to mention that the nonlinear MMSE LSA estimator was believed not to achieve substantial improvements compared to the MMSE LSA estimator without SPU estimation. This, however, could not be confirmed by our simulations, supported by a signal-component-wise subjective and instrumental evaluation.