Before revision:  For the diversity of temporal resolution in embedding processing, we consider dilation on TDNN-F, a variant of 1D-CNN .  Each stream stacks narrower TDNN-F layers whose kernel has a unique, stream-specific dilation rate when processing input speech frames in parallel. Hence it can better represent acoustic events without the increase of model complexity .
After revision:  For the diversity of temporal resolution in embedding processing, we consider dilation on TDNN-F, a variant of 1D-CNN . Each stream stacks narrower TDNN-F layers (a variant of 1D CNN), and output embedding vectors from the streams are concatenated then projected to the final layer .