12 citations · 20 across the 6 of their papers we have counts for
9 papers
Locate This, Not That: Class-Conditioned Sound Event DOA Estimation
Olga Slizovskaia, Gordon Wichern, Zhong-Qiu Wang +1
Existing systems for sound event localization and detection (SELD) typically operate by estimating a source location for all classes at every time instant. In this paper, we propos…
Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
Yen-Ju Lu, Samuele Cornell, Xuankai Chang +5
This paper describes our submission to the L3DAS22 Challenge Task 1, which consists of speech enhancement with 3D Ambisonic microphones. The core of our approach combines Deep Neur…
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…
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…
Localization Based Sequential Grouping for Continuous Speech Separation
Zhong-Qiu Wang, DeLiang Wang
This study investigates robust speaker localization for con-tinuous speech separation and speaker diarization, where we use speaker directions to group non-contiguous segments of t…
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)…