Low-complexity Post-processing Method for Speech Enhancement

In this paper, we propose a low-complexity post-processing method for speech enhancement. This real-time postprocessing method considers two gains, obtained by conventional log-spectral Minimum Mean-Square Error (LogMMSE) and neural network-based speech enhancement algorithms, respectively. These two gains are combined by an adaptive factor to share the advantages of these two kinds of enhancement algorithms. The harmonic structure of speech signal is further recovered by applying a harmonic gain calculated by the signal spectra and adaptive factor. Experimental results show that the proposed post-processing method achieves better performances in terms of speech quality.