DCCRN: Deep complex convolution recurrent network for phase-aware speech enhancement

Y Hu, Y Liu, S Lv, M ** with gated convolutional recurrent networks for monaural speech enhancement
K Tan, DL Wang - IEEE/ACM Transactions on Audio, Speech …, 2019 - ieeexplore.ieee.org
Phase is important for perceptual quality of speech. However, it seems intractable to directly
estimate phase spectra through supervised learning due to their lack of spectrotemporal …

A survey on audio diffusion models: Text to speech synthesis and enhancement in generative ai

C Zhang, C Zhang, S Zheng, M Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
Generative AI has demonstrated impressive performance in various fields, among which
speech synthesis is an interesting direction. With the diffusion model as the most popular …

Metricgan: Generative adversarial networks based black-box metric scores optimization for speech enhancement

SW Fu, CF Liao, Y Tsao, SD Lin - … Conference on Machine …, 2019 - proceedings.mlr.press
Adversarial loss in a conditional generative adversarial network (GAN) is not designed to
directly optimize evaluation metrics of a target task, and thus, may not always guide the …

Deep neural network techniques for monaural speech enhancement and separation: state of the art analysis

P Ochieng - Artificial Intelligence Review, 2023 - Springer
Deep neural networks (DNN) techniques have become pervasive in domains such as
natural language processing and computer vision. They have achieved great success in …