Optimization scheme of joint noise suppression and dereverberation based on higher-order statistics

In this paper, we apply the higher-order statistics parameter to automatically improve the performance of blind speech enhancement. Recently, a method to suppress both diffuse background noise and late reverberation part of speech has been proposed combining blind signal extraction and Wiener filtering. However, this method requires a good strategy for choosing the set of its parameters in order to achieve the optimum result and to control the amount of musical noise, which is a common problem in non-linear signal processing. We present an optimization scheme to control the value of Wiener filter coefficients used in this method, which depends on the amount of musical noise generated, measured by higher-order statistics. The noise reduction rate and cepstral distortion are also evaluated to confirm the effectiveness of this scheme.