  Sub-band models have achieved promising results due to their ability to model
local patterns in the spectrogram. Some studies further improve the performance
by fusing sub-band and full-band information. However, the structure for the
full-band and sub-band fusion model was not fully explored. This paper proposes
a dual-path transformer-based full-band and sub-band fusion network (DPT-FSNet)
for speech enhancement in the frequency domain. The intra and inter parts of
the dual-path transformer model sub-band and full-band information,
respectively. The features utilized by our proposed method are more
interpretable than those utilized by the time-domain dual-path transformer. We
conducted experiments on the Voice Bank + DEMAND and Interspeech 2020 Deep
Noise Suppression (DNS) datasets to evaluate the proposed method. Experimental
results show that the proposed method outperforms the current state-of-the-art.
