activity
20152021
most citedJoint Extraction of Entities and Relations Based on a Novel Tagging Scheme

106 citations · 165 across the 16 of their papers we have counts for

collaborators

26 papers

eess.AS2021

WASE: Learning When to Attend for Speaker Extraction in Cocktail Party Environments

Yunzhe Hao, Jiaming Xu, Peng Zhang +1

In the speaker extraction problem, it is found that additional information from the target speaker contributes to the tracking and extraction of the target speaker, which includes…

cs.SD20211 cited

MIMO Self-attentive RNN Beamformer for Multi-speaker Speech Separation

Xiyun Li, Yong Xu, Meng Yu +4

Recently, our proposed recurrent neural network (RNN) based all deep learning minimum variance distortionless response (ADL-MVDR) beamformer method yielded superior performance ove…

cs.SD2021

Speaker and Direction Inferred Dual-channel Speech Separation

Chenxing Li, Jiaming Xu, Nima Mesgarani +1

Most speech separation methods, trying to separate all channel sources simultaneously, are still far from having enough general- ization capabilities for real scenarios where the n…

cs.SD202114 cited

Exploring wav2vec 2.0 on speaker verification and language identification

Zhiyun Fan, Meng Li, Shiyu Zhou +1

Wav2vec 2.0 is a recently proposed self-supervised framework for speech representation learning. It follows a two-stage training process of pre-training and fine-tuning, and perfor…

cs.CL2020

CIF-based Collaborative Decoding for End-to-end Contextual Speech Recognition

Minglun Han, Linhao Dong, Shiyu Zhou +1

End-to-end (E2E) models have achieved promising results on multiple speech recognition benchmarks, and shown the potential to become the mainstream. However, the unified structure…

cs.SD20203 cited

Audio-visual Speech Separation with Adversarially Disentangled Visual Representation

Peng Zhang, Jiaming Xu, Jing shi +2

Speech separation aims to separate individual voice from an audio mixture of multiple simultaneous talkers. Although audio-only approaches achieve satisfactory performance, they bu…