  Time-domain speech enhancement (SE) has recently been intensively
investigated. Among recent works, DEMUCS introduces multi-resolution STFT loss
to enhance performance. However, some resolutions used for STFT contain
non-stationary signals, and it is challenging to learn multi-resolution
frequency losses simultaneously with only one output. For better use of
multi-resolution frequency information, we supplement multiple spectrograms in
different frame lengths into the time-domain encoders. They extract stationary
frequency information in both narrowband and wideband. We also adopt multiple
decoder outputs, each of which computes its corresponding resolution frequency
loss. Experimental results show that (1) it is more effective to fuse
stationary frequency features than non-stationary features in the encoder, and
(2) the multiple outputs consistent with the frequency loss improve
performance. Experiments on the Voice-Bank dataset show that the proposed
method obtained a 0.14 PESQ improvement.
