Speech enhancement using minimum mean-square error estimation and a post-filter derived from vector quantization of clean speech

摘要

In this paper, a novel post-filtering method applied after the logSTSA filter is proposed. Since the post-filter is derived from vector quantization of clean speech database, it has an equivalent effect of imposing clean source spectral constraints on the enhanced speech. When combined with the logSTSA filter, the additional filter can noticeably suppress residual artifacts by effectively lowering the residual white noise of decision-directed estimation as well as reducing the musical noise of maximum likelihood estimation. Compared to the logSTSA enhanced speech, the overall enhanced speech is able to raise the PESQ score by nearly half a point.