1 citations · 1 across the 4 of their papers we have counts for
5 papers
An Adapter based Multi-label Pre-training for Speech Separation and Enhancement
Tianrui Wang, Xie Chen, Zhuo Chen +2
In recent years, self-supervised learning (SSL) has achieved tremendous success in various speech tasks due to its power to extract representations from massive unlabeled data. How…
Multiple Confidence Gates For Joint Training Of SE And ASR
Tianrui Wang, Weibin Zhu, Yingying Gao +2
Joint training of speech enhancement model (SE) and speech recognition model (ASR) is a common solution for robust ASR in noisy environments. SE focuses on improving the auditory q…
Harmonic gated compensation network plus for ICASSP 2022 DNS CHALLENGE
Tianrui Wang, Weibin Zhu, Yingying Gao +3
The harmonic structure of speech is resistant to noise, but the harmonics may still be partially masked by noise. Therefore, we previously proposed a harmonic gated compensation ne…
HGCN: Harmonic gated compensation network for speech enhancement
Tianrui Wang, Weibin Zhu, Yingying Gao +2
Mask processing in the time-frequency (T-F) domain through the neural network has been one of the mainstreams for single-channel speech enhancement. However, it is hard for most mo…
A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement
Tianrui Wang, Weibin Zhu
Deep learning technology has been widely applied to speech enhancement. While testing the effectiveness of various network structures, researchers are also exploring the improvemen…