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.

翻译：以自动编码器为基础的编码器代码器使用量子化来将其瓶颈层激活转化为比特字符串,这一过程阻碍编码器和解码器部分之间的信息流动。 为回避这一问题, 我们使用额外的跳过对应的编码器- 解码器层之间的连接。 假设是, 在镜像式自动编码器表层中, 一个解码器层重建了相应的编码器层的中间特征。 因此, 从相应的编码器层直接传播的任何额外信息都有助于重建。 我们以额外的自动编码器的形式实施这种跳过连接, 每一个都是一个小编码器, 压缩配对的编码器- 解码器层之间的大规模数据传输。 我们通过实验来核实, 拟议的超自动编码结构提高了听觉质量, 而不是普通的自动编码基线 。