Snore-GANs: Improving Automatic Snore Sound Classification With Synthesized Data
Snore-GANs: Improving Automatic Snore Sound Classification With Synthesized Data
One of the frontier issues that severely hamper the development of automatic snore sound classification (ASSC) associates to the lack of sufficient supervised training data. To cope with this problem, we propose a novel data augmentation approach based on semi-supervised conditional generative adversarial networks (scGANs), which aims to automatically learn …