activity
20202023
most citedTdcgan: Temporal Dilated Convolutional Generative Adversarial Network for End-to-end Speech Enhancement

6 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2023★ 1 cited

Large-Scale Learning on Overlapped Speech Detection: New Benchmark and New General System

Zhaohui Yin, Jingguang Tian, Xinhui Hu +2

Overlapped Speech Detection (OSD) is an important part of speech applications involving analysis of multi-party conversations. However, most of existing OSD systems are trained and…

cs.CL2022★ 3 cited

Hybrid-Regressive Neural Machine Translation

Qiang Wang, Xinhui Hu, Ming Chen

In this work, we empirically confirm that non-autoregressive translation with an iterative refinement mechanism (IR-NAT) suffers from poor acceleration robustness because it is mor…

cs.SD2022

The Royalflush System for VoxCeleb Speaker Recognition Challenge 2022

Jingguang Tian, Xinhui Hu, Xinkang Xu

In this technical report, we describe the Royalflush submissions for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). Our submissions contain track 1, which is for supe…

cs.SD2022

The RoyalFlush System of Speech Recognition for M2MeT Challenge

Shuaishuai Ye, Peiyao Wang, Shunfei Chen +2

This paper describes our RoyalFlush system for the track of multi-speaker automatic speech recognition (ASR) in the M2MeT challenge. We adopted the serialized output training (SOT)…

cs.SD2022★ 4 cited

Royalflush Speaker Diarization System for ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge

Jingguang Tian, Xinhui Hu, Xinkang Xu

This paper describes the Royalflush speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription Challenge(M2MeT). Our system comprises speech enhanc…

eess.AS2020★ 6 cited

Tdcgan: Temporal Dilated Convolutional Generative Adversarial Network for End-to-end Speech Enhancement

Shuaishuai Ye, Xinhui Hu, Xinkang Xu

In this paper, in order to further deal with the performance degradation caused by ignoring the phase information in conventional speech enhancement systems, we proposed a temporal…