  Large-scale mobile communication systems tend to contain legacy transmission
channels with narrowband bottlenecks, resulting in characteristic
"telephone-quality" audio. While higher quality codecs exist, due to the scale
and heterogeneity of the networks, transmitting higher sample rate audio with
modern high-quality audio codecs can be difficult in practice. This paper
proposes an approach where a communication node can instead extend the
bandwidth of a band-limited incoming speech signal that may have been passed
through a low-rate codec. To this end, we propose a WaveNet-based model
conditioned on a log-mel spectrogram representation of a bandwidth-constrained
speech audio signal of 8 kHz and audio with artifacts from GSM full-rate (FR)
compression to reconstruct the higher-resolution signal. In our experimental
MUSHRA evaluation, we show that a model trained to upsample to 24kHz speech
signals from audio passed through the 8kHz GSM-FR codec is able to reconstruct
audio only slightly lower in quality to that of the Adaptive Multi-Rate
Wideband audio codec (AMR-WB) codec at 16kHz, and closes around half the gap in
perceptual quality between the original encoded signal and the original speech
sampled at 24kHz. We further show that when the same model is passed 8kHz audio
that has not been compressed, is able to again reconstruct audio of slightly
better quality than 16kHz AMR-WB, in the same MUSHRA evaluation.
