Accurate recognition of cocktail party speech containing overlapping
spe...
Automatic recognition of disordered and elderly speech remains highly
ch...
Rich sources of variability in natural speech present significant challe...
Current ASR systems are mainly trained and evaluated at the utterance le...
A key challenge in dysarthric speech recognition is the speaker-level
di...
As a common way of emotion signaling via non-linguistic vocalizations, v...
With the global population aging rapidly, Alzheimer's disease (AD) is
pa...
Automatic recognition of disordered and elderly speech remains a highly
...
Speaker adaptation techniques provide a powerful solution to customise
a...
Modeling the speaker variability is a key challenge for automatic speech...
Automatic recognition of disordered speech remains a highly challenging ...
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating
p...
We propose an unsupervised learning method to disentangle speech into co...
State-of-the-art neural network language models (NNLMs) represented by l...
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating
p...
A key challenge for automatic speech recognition (ASR) systems is to mod...
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating
p...
State of the art time automatic speech recognition (ASR) systems are bec...
Fundamental modelling differences between hybrid and end-to-end (E2E)
au...
Articulatory features are inherently invariant to acoustic signal distor...
Despite the rapid progress of automatic speech recognition (ASR) technol...
Despite the rapid advance of automatic speech recognition (ASR) technolo...
Deep neural networks have brought significant advancements to speech emo...
Automatic recognition of dysarthric and elderly speech highly challengin...
Articulatory features are inherently invariant to acoustic signal distor...
Despite the rapid progress of automatic speech recognition (ASR) technol...
Dysarthric speech reconstruction (DSR), which aims to improve the qualit...
Though significant progress has been made for speaker-dependent
Video-to...
The Mandarin Chinese language is known to be strongly influenced by a ri...
Dysarthric speech recognition is a challenging task due to acoustic
vari...
Despite the rapid progress of automatic speech recognition (ASR) technol...
Disordered speech recognition is a highly challenging task. The underlyi...
Automatic recognition of disordered speech remains a highly challenging ...
State-of-the-art automatic speech recognition (ASR) system development i...
State-of-the-art language models (LMs) represented by long-short term me...
Recognition of overlapped speech has been a highly challenging task to d...
State-of-the-art neural language models represented by Transformers are
...
The high memory consumption and computational costs of Recurrent neural
...
Automatic recognition of disordered speech remains a highly challenging ...
Existing approaches for anti-spoofing in automatic speaker verification ...
This paper describes a variational auto-encoder based non-autoregressive...
One-shot voice conversion (VC), which performs conversion across arbitra...
Dysarthric speech detection (DSD) systems aim to detect characteristics ...
State-of-the-art neural language models (LMs) represented by Transformer...
A key task for speech recognition systems is to reduce the mismatch betw...
Existing approaches for replay and synthetic speech detection still lack...
This paper proposes an any-to-many location-relative, sequence-to-sequen...
Controversy exists on whether differentiable neural architecture search
...
Deep neural networks (DNNs) based automatic speech recognition (ASR) sys...
Recently adversarial attacks on automatic speaker verification (ASV) sys...