Generative adversarial networks (GANs) have seen remarkable progress in recent years.
They are used as generative models for all kinds of data such as text, images, audio, music …

Deep neural networks (DNN) techniques have become pervasive in domains such as
natural language processing and computer vision. They have achieved great success in …

Noisy situations cause huge problems for the hearing-impaired, as hearing aids often make
speech more audible but do not always restore intelligibility. In noisy settings, humans …

In actual industrial environment, intelligent diagnosis method requires a sufficient number of
samples to ensure application effect. However, once industrial system fails, it usually stops …

We investigate supervised learning strategies that improve the training of neural network
audio classifiers on small annotated collections. In particular, we study whether (i) a naive …

The accuracy of voice or speech recognition is affected due to the presence of various
background noises present in the surroundings. Automatic Speech Recognition …

As a category of transfer learning, domain adaptation plays an important role in generalizing
the model trained in one task and applying it to other similar tasks or settings. In speech …

The speech enhancement task usually consists of removing additive noise or reverberation
that partially mask spoken utterances, affecting their intelligibility. However, little attention is …

Noise fitting plays a key role in underwater acoustic communications. Traditional
approximate models can fit global heavy-tail distribution of the impulsive noise with fixed …

Speech enhancement aims to improve the quality and intelligibility of speech signals, which
is a challenging task in adverse environments. Speech enhancement generative adversarial …