activity
20182021
most citedDivide and Conquer: A Deep CASA Approach to Talker-independent Monaural Speaker Separation

5 citations · 20 across the 6 of their papers we have counts for

collaborators

11 papers

eess.AS20213 cited

Multi-Channel and Multi-Microphone Acoustic Echo Cancellation Using A Deep Learning Based Approach

Hao Zhang, DeLiang Wang

Building on the deep learning based acoustic echo cancellation (AEC) in the single-loudspeaker (single-channel) and single-microphone setup, this paper investigates multi-channel A…

cs.CL20203 cited

Efficient End-to-End Speech Recognition Using Performers in Conformers

Peidong Wang, DeLiang Wang

On-device end-to-end speech recognition poses a high requirement on model efficiency. Most prior works improve the efficiency by reducing model sizes. We propose to reduce the comp…

eess.AS20201 cited

Complex ratio masking for singing voice separation

Yixuan Zhang, Yuzhou Liu, DeLiang Wang

Music source separation is important for applications such as karaoke and remixing. Much of previous research focuses on estimating short-time Fourier transform (STFT) magnitude an…

cs.SD2020

Speaker Separation Using Speaker Inventories and Estimated Speech

Peidong Wang, Zhuo Chen, DeLiang Wang +2

We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation. SSUSIES…

eess.AS2020

Dense CNN with Self-Attention for Time-Domain Speech Enhancement

Ashutosh Pandey, DeLiang Wang

Speech enhancement in the time domain is becoming increasingly popular in recent years, due to its capability to jointly enhance both the magnitude and the phase of speech. In this…

eess.AS20204 cited

Multi-Microphone Complex Spectral Mapping for Speech Dereverberation

Zhong-Qiu Wang, DeLiang Wang

This study proposes a multi-microphone complex spectral mapping approach for speech dereverberation on a fixed array geometry. In the proposed approach, a deep neural network (DNN)…