Thomas Lotter

Single- and Multi-Microphone Spectral Amplitude Estimation Using a Super-Gaussian Speech Model

In this contribution, MAP spectral amplitude estimators for speech enhancement are presented. For single-microphone applications, efficient MAP estimators with a super-Gaussian speech model, that can be adapted with high accuracy towards the real distribution in a given system, are introduced. For multi-microphone applications, joint MAP estimators that also exploit spatial properties of speech and noise are derived. Both the integration of the more accurate speech model as well as the multi-microphone joint spectral amplitude estimation improve the performance of a common DFT domain speech enhancement system.