Speech signal enhancement achieves high-level performance in recent years using deep
learning techniques. However, the deep learning technique in the speech enhancement …

Recently, deep neural networks (DNNs) were successfully introduced to the speech
enhancement area. Conventional DNN-based algorithms generally produce over-smoothed …

Speech enhancement is fundamental for various real time speech applications and it is a
challenging task in the case of a single channel because practically only one data channel …

While deep learning based speech enhancement systems have made rapid progress in
improving the quality of speech signals, they can still produce outputs that contain artifacts …

This paper proposes a novel fully convolutional neural network (FCN) called FLGCNN to
address the end-to-end speech enhancement in time domain. The proposed FLGCNN is …

Speech enhancement methods usually suffer from speech distortion problem, which leads to
the enhanced speech losing so much significant speech information. This damages the …

Convolutional neural network (CNN) based methods, such as the convolutional encoder–
decoder network, offer state-of-the-art results in monaural speech enhancement. In the …

Recently, progressive learning has shown its capacity to improve speech quality and speech
intelligibility when it is combined with deep neural network (DNN) and long short-term …

Speech enhancement is an essential task for improving the quality and intelligibility of
speech signals corrupted by noise. Current deep neural network-based speech …

Monaural speech enhancement aims to remove background noise from an audio recording
containing speech in order to improve its clarity and intelligibility. Currently, the most …