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20192022
most citedRecent Progress in the CUHK Dysarthric Speech Recognition System

93 citations · 213 across the 14 of their papers we have counts for

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13 papers · 1 filter

eess.AS20235 cited

Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression

Hangting Chen, Jianwei Yu, Yi Luo +4

Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning mode…

eess.AS2023

The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track

Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai +24

This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music so…

eess.AS2022

Music Source Separation with Band-split RNN

Yi Luo, Jianwei Yu

The performance of music source separation (MSS) models has been greatly improved in recent years thanks to the development of novel neural network architectures and training pipel…

eess.AS202293 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.AS20212 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.AS2021

TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation

Helin Wang, Bo Wu, Lianwu Chen +7

In this paper, we exploit the effective way to leverage contextual information to improve the speech dereverberation performance in real-world reverberant environments. We propose…