  In multichannel speech enhancement, both spectral and spatial information are
vital for discriminating between speech and noise. How to fully exploit these
two types of information and their temporal dynamics remains an interesting
research problem. As a solution to this problem, this paper proposes a
multi-cue fusion network named McNet, which cascades four modules to
respectively exploit the full-band spatial, narrow-band spatial, sub-band
spectral, and full-band spectral information. Experiments show that each module
in the proposed network has its unique contribution and, as a whole, notably
outperforms other state-of-the-art methods.
