Light-Weight Self-Attention Augmented Generative Adversarial Networks for Speech Enhancement
Generative adversarial networks (GANs) have shown their superiority for speech enhancement. Nevertheless, most previous attempts had convolutional layers as the backbone, which may obscure long-range dependencies across an input sequence due to the convolution operator’s local receptive field. One p...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
|
| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/10/13/1586 |