activity
20202023
most citedRecent Progress in the CUHK Dysarthric Speech Recognition System

93 citations · 187 across the 13 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

eess.AS2022

A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion

Xu Li, Shansong Liu, Ying Shan

Typically, singing voice conversion (SVC) depends on an embedding vector, extracted from either a speaker lookup table (LUT) or a speaker recognition network (SRN), to model speake…

eess.AS2022

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…

eess.AS2022★ 93 cited

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…

cs.SD2022★ 52 cited

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…

cs.SD2022★ 16 cited

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…

eess.AS2022★ 1 cited

Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks

Shoukang Hu, Xurong Xie, Mingyu Cui +6

State-of-the-art automatic speech recognition (ASR) system development is data and computation intensive. The optimal design of deep neural networks (DNNs) for these systems often…