In this article a new neural network for speech enhancement is proposed where single-
channel noisy speech is processed in order to improve its intelligibility and quality. It is …

Speech enhancement performance is highly reliant on on the efficacy of representative
features extracted from noisy speech. However, SE frequently experiences problems with …

When designing fully-convolutional neural network, there is a trade-off between receptive
field size, number of parameters and spatial resolution of features in deeper layers of the …

Deep neural networks have significantly promoted the progress of speech enhancement
technology. However, a great number of speech enhancement approaches are unable to …

In this paper a recurrent U-net neural architecture is proposed to speech enhancement. The
mentioned neural network architecture is trained to provide a mapping between a …

Over the past ten years, deep learning has enabled significant advancements in the
improvement of noisy speech. Due to the short time stability of speech signal, previous …

Over the past 10 years, deep learning has enabled significant advancements in the
improvement of noisy speech. In an end-to-end speech enhancement, the deep neural …

Deep learning (DL) networks have grown into powerful alternatives for speech
enhancement and have achieved excellent results by improving speech quality …

This paper proposes a deep learning-based densely connected Y-Net as an effective
network architecture for the fusion of time and frequency domain loss functions for speech …

In this paper, we considered the problem of the speech enhancement similar to the real-
world environments where several complex noise sources simultaneously degrade the …