In multimedia intelligent systems, speech enhancement is commonly employed to improve
the quality of speech signals, making them clearer and more natural. Current deep learning …

Estimating noise information exactly is crucial for noise aware training in speech
applications including speech enhancement (SE) which is our focus in this paper. To …

Most of the deep learning based speech enhancement methods focus on the modeling of
complicated relationship between the noisy speech and the clean speech without the …

With recent advances of diffusion model, generative speech enhancement (SE) has
attracted a surge of research interest due to its great potential for unseen testing noises …

Speech enhancement is challenging because of the diversity of background noise types.
Most of the existing methods are focused on modelling the speech rather than the noise. In …

Data-driven speech enhancement employing deep neural networks (DNNs) can provide
state-of-the-art performance even in the presence of non-stationary noise. During the …

In various real-world scenarios, ambient noise is often present, highlighting the critical role
of speech enhancement in optimising speech signal quality. Understanding the …

Speech enhancement is a task to improve the intelligibility and perceptual quality of
degraded speech signal. Recently, neural networks based methods have been applied to …

The performance of speech enhancement algorithms can be further improved by
considering the application scenarios of speech products. In this paper, we propose an …

Noise statistics and speech spectrum characteristics are the essential information for the
single channel speech enhancement. The signal processing-based methods mainly rely on …