Inverse filtering and principal component analysis techniques for speech dereverberation

Abstract

In this work, we present a single channel approach for early and late reverberation suppression. This approach can be decomposed into two stages. The first stage employs the inverse filter to augment the signal-to-reverberant energy ratio. The second stage uses the kernel PCA algorithm to enhance the obtained dereverberant signal. It consists in extracting the main non-linear features from the speech signal after inverse filtering. Our approach appears to be efficient mainly in far field conditions and in highly reverberant environments.