  An autoencoder-based codec employs quantization to turn its bottleneck layer
activation into bitstrings, a process that hinders information flow between the
encoder and decoder parts. To circumvent this issue, we employ additional skip
connections between the corresponding pair of encoder-decoder layers. The
assumption is that, in a mirrored autoencoder topology, a decoder layer
reconstructs the intermediate feature representation of its corresponding
encoder layer. Hence, any additional information directly propagated from the
corresponding encoder layer helps the reconstruction. We implement this kind of
skip connections in the form of additional autoencoders, each of which is a
small codec that compresses the massive data transfer between the paired
encoder-decoder layers. We empirically verify that the proposed
hyper-autoencoded architecture improves perceptual audio quality compared to an
ordinary autoencoder baseline.
