138 citations · 792 across the 57 of their papers we have counts for
5 papers · 1 filter
CWS-PResUNet: Music Source Separation with Channel-wise Subband Phase-aware ResUNet
Haohe Liu, Qiuqiang Kong, Jiafeng Liu
Music source separation (MSS) shows active progress with deep learning models in recent years. Many MSS models perform separations on spectrograms by estimating bounded ratio masks…
VoiceFixer: Toward General Speech Restoration with Neural Vocoder
Haohe Liu, Qiuqiang Kong, Qiao Tian +4
Speech restoration aims to remove distortions in speech signals. Prior methods mainly focus on single-task speech restoration (SSR), such as speech denoising or speech declipping.…
Decoupling Magnitude and Phase Estimation with Deep ResUNet for Music Source Separation
Qiuqiang Kong, Yin Cao, Haohe Liu +2
Deep neural network based methods have been successfully applied to music source separation. They typically learn a mapping from a mixture spectrogram to a set of source spectrogra…
Joint Echo Cancellation and Noise Suppression based on Cascaded Magnitude and Complex Mask Estimation
Xiaofeng Shu, Yehang Zhu, Yanjie Chen +4
Acoustic echo and background noise can seriously degrade the intelligibility of speech. In practice, echo and noise suppression are usually treated as two separated tasks and can b…
Speech enhancement with weakly labelled data from AudioSet
Qiuqiang Kong, Haohe Liu, Xingjian Du +3
Speech enhancement is a task to improve the intelligibility and perceptual quality of degraded speech signal. Recently, neural networks based methods have been applied to speech en…