94 citations · 305 across the 37 of their papers we have counts for
38 papers
Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment
Yiwen Shao, Shi-Xiong Zhang, Yong Xu +4
In the field of multi-channel, multi-speaker Automatic Speech Recognition (ASR), the task of discerning and accurately transcribing a target speaker's speech within background nois…
Deep Audio Zooming: Beamwidth-Controllable Neural Beamformer
Meng Yu, Dong Yu
Audio zooming, a signal processing technique, enables selective focusing and enhancement of sound signals from a specified region, attenuating others. While traditional beamforming…
Hybrid AHS: A Hybrid of Kalman Filter and Deep Learning for Acoustic Howling Suppression
Hao Zhang, Meng Yu, Yuzhong Wu +2
Deep learning has been recently introduced for efficient acoustic howling suppression (AHS). However, the recurrent nature of howling creates a mismatch between offline training an…
Deep Learning for Joint Acoustic Echo and Acoustic Howling Suppression in Hybrid Meetings
Hao Zhang, Meng Yu, Dong Yu
Hybrid meetings have become increasingly necessary during the post-COVID period and also brought new challenges for solving audio-related problems. In particular, the interplay bet…
Deep AHS: A Deep Learning Approach to Acoustic Howling Suppression
Hao Zhang, Meng Yu, Dong Yu
In this paper, we formulate acoustic howling suppression (AHS) as a supervised learning problem and propose a deep learning approach, called Deep AHS, to address it. Deep AHS is tr…
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…