Multi-stage learning is an effective technique for invoking multiple deep-learning modules
sequentially. This paper applies multi-stage learning to speech enhancement by using a …

Speech enhancement is an important method for improving speech quality and intelligibility
in noisy environments. An effective speech enhancement model depends on precise …

The recent development of speech enhancement methods has incorporated attention
mechanisms for learning long-term speech signal dependencies. The utilization of deep …

Automated classification of respiratory sounds has become an active research area in recent
years. While recent studies have utilised deep learning methods to aid with respiratory …

In speech enhancement tasks, local and non-local attention mechanisms have been
significantly improved and well studied. However, a natural speech signal contains many …

Recently channel attention mechanism playing a major role in improving the performance of
deep convolution neural networks. Even though there is an improvement in the …

The use of Transformer architectures has facilitated remarkable progress in speech
enhancement. Training Transformers using substantially long speech utterances is often …

In this paper, we present a fully convolutional neural network for enhancing real-time speech
in the time domain. Skip connections are included in the architecture of the proposed …

Speech enhancement system is applied in many devices such as hearing aids. To improve
speech quality retrieved from noisy observations, this paper proposes a two-stage network …

Speech enhancement is crucial in many speech processing applications. Recently,
researchers have been exploring ways to improve performance by effectively capturing the …