A Novel Noise Robust Front-End Using First Order VTS in Construction of Mel-Warped Wiener Filter

In this paper, we first review two approaches in the context of robust recognition, e.g. speech enhancement based two-stage mel-warp Wiener filtering (MWF) (A. Agarwal and Y.M. Cheng, 1999) and first-order vector Taylor series (VTS) (P.J. Moreno et al., 1996) compensation in log power spectrum, which are widely used. A new noise robust front-end is proposed, in which VTS compensation derived statistics are used to construct the mel-warped Wiener filter. We will show that this noise robust front end is superior. The experiments results prove that our proposed method does show significant improvement over VTS and MWF