Meetings are an essential form of communication for all types of
organiz...
Recently, deep learning (DL)-based non-intrusive speech assessment model...
Speech enhancement (SE) performance has improved considerably since the ...
Although deep learning (DL) has achieved notable progress in speech
enha...
Numerous compression and acceleration strategies have achieved outstandi...
In this study, we propose a cross-domain multi-objective speech assessme...
Most of the deep learning-based speech enhancement models are learned in...
SpeechBrain is an open-source and all-in-one speech toolkit. It is desig...
The discrepancy between the cost function used for training a speech
enh...
The calculation of most objective speech intelligibility assessment metr...
Speech enhancement (SE) aims to improve speech quality and intelligibili...
The Transformer architecture has shown its superior ability than recurre...
The intelligibility of natural speech is seriously degraded when exposed...
Integrating modalities, such as video signals with speech, has been show...
Speech perception is a key to verbal communication. For people with hear...
The combined electric and acoustic stimulation (EAS) has demonstrated be...
In recent years, waveform-mapping-based speech enhancement (SE) methods ...
Most recent studies on deep learning based speech enhancement (SE) focus...
Adversarial loss in a conditional generative adversarial network (GAN) i...
Utilizing a human-perception-related objective function to train a speec...
Existing objective evaluation metrics for voice conversion (VC) are not
...
Numerous studies have investigated the effectiveness of neural network
q...
Nowadays, most of the objective speech quality assessment tools (e.g.,
p...
Speech enhancement model is used to map a noisy speech to a clean speech...
This paper aims to address two issues existing in the current speech
enh...
This study proposes a fully convolutional network (FCN) model for raw
wa...