The compare between two DNN-based signal suppression methods
TaiWei Cui · 2022
In this article, the efficiency of two methods of speech enhancement algorithm, both of which used Deep Neural Network, are compared. The first method is based on mapping and the second one based on masking. For the method based on mapping, the input of the network is the power spectrum of noisy signal and figure out the power spectrum of suppressed signal. For the algorithm based on masking, the input is the Time-Frequency spectral of noisy signal, and then figure out the Ideal Ratio Masking (IRM) of the signal. And by multiply the element of IRM matrix with the corresponding element of spectral, the signal of pure speech is expected to be got. And the compare of the PESQ scores of the ideal signal and the result figured by the different methods shows, that in the method based on the masking performs better.