58 citations · 335 across the 31 of their papers we have counts for
31 papers
Multi-resolution location-based training for multi-channel continuous speech separation
Hassan Taherian, DeLiang Wang
The performance of automatic speech recognition (ASR) systems severely degrades when multi-talker speech overlap occurs. In meeting environments, speech separation is typically per…
NeuralKalman: A Learnable Kalman Filter for Acoustic Echo Cancellation
Yixuan Zhang, Meng Yu, Hao Zhang +2
The robustness of the Kalman filter to double talk and its rapid convergence make it a popular approach for addressing acoustic echo cancellation (AEC) challenges. However, the ina…
Time-Domain Speech Enhancement for Robust Automatic Speech Recognition
Yufeng Yang, Ashutosh Pandey, DeLiang Wang
It has been shown that the intelligibility of noisy speech can be improved by speech enhancement algorithms. However, speech enhancement has not been established as an effective fr…
VoiceFixer: A Unified Framework for High-Fidelity Speech Restoration
Haohe Liu, Xubo Liu, Qiuqiang Kong +5
Speech restoration aims to remove distortions in speech signals. Prior methods mainly focus on a single type of distortion, such as speech denoising or dereverberation. However, sp…
Neural Vocoder is All You Need for Speech Super-resolution
Haohe Liu, Woosung Choi, Xubo Liu +3
Speech super-resolution (SR) is a task to increase speech sampling rate by generating high-frequency components. Existing speech SR methods are trained in constrained experimental…
A Conformer Based Acoustic Model for Robust Automatic Speech Recognition
Yufeng Yang, Peidong Wang, DeLiang Wang
This study addresses robust automatic speech recognition (ASR) by introducing a Conformer-based acoustic model. The proposed model builds on the wide residual bi-directional long s…