104 citations · 305 across the 50 of their papers we have counts for
5 papers · 1 filter
The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks
Darius Petermann, Gordon Wichern, Zhong-Qiu Wang +1
The cocktail party problem aims at isolating any source of interest within a complex acoustic scene, and has long inspired audio source separation research. Recent efforts have mai…
Leveraging Low-Distortion Target Estimates for Improved Speech Enhancement
Zhong-Qiu Wang, Gordon Wichern, Jonathan Le Roux
A promising approach for multi-microphone speech separation involves two deep neural networks (DNN), where the predicted target speech from the first DNN is used to compute signal…
On The Compensation Between Magnitude and Phase in Speech Separation
Zhong-Qiu Wang, Gordon Wichern, Jonathan Le Roux
Deep neural network (DNN) based end-to-end optimization in the complex time-frequency (T-F) domain or time domain has shown considerable potential in monaural speech separation. Ma…
Convolutive Prediction for Reverberant Speech Separation
Zhong-Qiu Wang, Gordon Wichern, Jonathan Le Roux
We investigate the effectiveness of convolutive prediction, a novel formulation of linear prediction for speech dereverberation, for speaker separation in reverberant conditions. T…
Convolutive Prediction for Monaural Speech Dereverberation and Noisy-Reverberant Speaker Separation
Zhong-Qiu Wang, Gordon Wichern, Jonathan Le Roux
A promising approach for speech dereverberation is based on supervised learning, where a deep neural network (DNN) is trained to predict the direct sound from noisy-reverberant spe…