TME_Audio_Super-Resolution_Samples

Audio samples for the paper 'Phase-aware music super-resolution using generative adversarial networks'

Ground_Truth_HR: high-resolution (HR) audio

Ground_Truth_LR: a low-resolution (LR) input audio

F-DNN: Fully-connected network implementation in the frequency domain

T-CNN: CNN implementation in the time domain

F-CNN: CNN (generator network of GAN) implementation in the frequency domain

Proposed: GAN implementation in the frequency domain for HB magnitude estimation and MelGAN implementation for HB phase estimation.

Phase Estimation methods

flip: the high-frequency phase is produced by flipping the phase of LFC (low frequency components) and adding a negative sign

gla: a modified version of GLA is used to maintain both the magnitudes and phase of LFC through the iteration process

melgan: HFC (high frequency components) phase is extracted and complemented by the give magnitudes as well as LFC information in order to obtain the final HR output