Convolutive Blind Signal Separation With Post-Processing

A new subband based speech enhancement scheme is presented. It integrates spatial and temporal signal processing methods to enhance speech signals in a noisy environment. The approach makes use of the popular blind signal separation (BSS) to spatially separate the target signal from the interference. Due to the multipath/reverberant environment, BSS has its fundamental limitation in its separation quality. To overcome that, an adaptive noise canceller (ANC) is employed to perform further interference reduction. The reference for the ANC in this case is simply the interference dominant output from the BSS. A higher order statistical method is proposed for the selection of the reference signal. This post processing acts as a spectral decorrelator and experimental results show that even in under-determined (more sources than elements) case, the structure offers impressive enhancement capability. Further, a remarkable improvement in recognition rate is registered when tested in automatic speech recognition (ASR).