Deep Residual-Dense Lattice Network for Speech Enhancement

Understand

Convolutional neural networks (CNNs) with residual links (ResNets) and causal dilated convolutional units have been the network of choice for deep learning approaches to speech enhancement.

• While residual links improve gradient flow during training, feature diminution of shallow layer outputs can occur due to repetitive summations with deeper layer outputs.
• One strategy to improve feature re-usage is to fuse both ResNets and densely connected CNNs (DenseNets).
• DenseNets, however, over-allocate parameters for feature re-usage.