  With active research in audio compression techniques yielding substantial
breakthroughs, spectral reconstruction of low-quality audio waves remains a
less indulged topic. In this paper, we propose a novel approach for
reconstructing higher frequencies from considerably longer sequences of
low-quality MP3 audio waves. Our technique involves inpainting audio
spectrograms with residually stacked autoencoder blocks by manipulating
individual amplitude and phase values in relation to perceptual differences.
Our architecture presents several bottlenecks while preserving the spectral
structure of the audio wave via skip-connections. We also compare several task
metrics and demonstrate our visual guide to loss selection. Moreover, we show
how to leverage differential quantization techniques to reduce the initial
model size by more than half while simultaneously reducing inference time,
which is crucial in real-world applications.
