93 citations · 176 across the 7 of their papers we have counts for
10 papers
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition
Shujie Hu, Shansong Liu, Xurong Xie +6
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems for normal spee…
Recent Progress in the CUHK Dysarthric Speech Recognition System
Shansong Liu, Mengzhe Geng, Shoukang Hu +5
Despite the rapid progress of automatic speech recognition (ASR) technologies in the past few decades, recognition of disordered speech remains a highly challenging task to date. D…
Investigation of Data Augmentation Techniques for Disordered Speech Recognition
Mengzhe Geng, Xurong Xie, Shansong Liu +4
Disordered speech recognition is a highly challenging task. The underlying neuro-motor conditions of people with speech disorders, often compounded with co-occurring physical disab…
Spectro-Temporal Deep Features for Disordered Speech Assessment and Recognition
Mengzhe Geng, Shansong Liu, Jianwei Yu +6
Automatic recognition of disordered speech remains a highly challenging task to date. Sources of variability commonly found in normal speech including accent, age or gender, when f…
Adversarial Data Augmentation for Disordered Speech Recognition
Zengrui Jin, Mengzhe Geng, Xurong Xie +4
Automatic recognition of disordered speech remains a highly challenging task to date. The underlying neuro-motor conditions, often compounded with co-occurring physical disabilitie…
Bayesian Transformer Language Models for Speech Recognition
Boyang Xue, Jianwei Yu, Junhao Xu +6
State-of-the-art neural language models (LMs) represented by Transformers are highly complex. Their use of fixed, deterministic parameter estimates fail to account for model uncert…