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20202023
most citedRecent Progress in the CUHK Dysarthric Speech Recognition System

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

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9 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…

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…

eess.AS2021★ 2 cited

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…

eess.AS2020★ 4 cited

Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition

Shoukang Hu, Xurong Xie, Shansong Liu +5

Discriminative training techniques define state-of-the-art performance for automatic speech recognition systems. However, they are inherently prone to overfitting, leading to poor…

eess.AS2020★ 2 cited

Audio-visual Multi-channel Integration and Recognition of Overlapped Speech

Jianwei Yu, Shi-Xiong Zhang, Bo Wu +6

Automatic speech recognition (ASR) technologies have been significantly advanced in the past few decades. However, recognition of overlapped speech remains a highly challenging tas…

eess.AS2020★ 2 cited

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

Shoukang Hu, Xurong Xie, Shansong Liu +4

Deep neural networks (DNNs) based automatic speech recognition (ASR) systems are often designed using expert knowledge and empirical evaluation. In this paper, a range of neural ar…

eess.AS2020★ 10 cited

Audio-visual Recognition of Overlapped speech for the LRS2 dataset

Jianwei Yu, Shi-Xiong Zhang, Jian Wu +7

Automatic recognition of overlapped speech remains a highly challenging task to date. Motivated by the bimodal nature of human speech perception, this paper investigates the use of…