CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement

Understand

In this work, we further develop the conformer-based metric generative adversarial network (CMGAN) model for speech enhancement (SE) in the time-frequency (TF) domain.

• This paper builds on our previous work but takes a more in-depth look by conducting extensive ablation studies on model inputs and architectural design choices.
• We rigorously tested the generalization ability of the model to unseen noise types and distortions.
• We have fortified our claims through DNS-MOS measurements and listening tests.