158 citations · 241 across the 23 of their papers we have counts for
23 papers
The FlySpeech Audio-Visual Speaker Diarization System for MISP Challenge 2022
Li Zhang, Huan Zhao, Yue Li +6
This paper describes the FlySpeech speaker diarization system submitted to the second \textbf{M}ultimodal \textbf{I}nformation Based \textbf{S}peech \textbf{P}rocessing~(\textbf{MI…
MC-SpEx: Towards Effective Speaker Extraction with Multi-Scale Interfusion and Conditional Speaker Modulation
Jun Chen, Wei Rao, Zilin Wang +5
The previous SpEx+ has yielded outstanding performance in speaker extraction and attracted much attention. However, it still encounters inadequate utilization of multi-scale inform…
Gesper: A Restoration-Enhancement Framework for General Speech Reconstruction
Wenzhe Liu, Yupeng Shi, Jun Chen +5
This paper describes a real-time General Speech Reconstruction (Gesper) system submitted to the ICASSP 2023 Speech Signal Improvement (SSI) Challenge. This novel proposed system is…
Inter-SubNet: Speech Enhancement with Subband Interaction
Jun Chen, Wei Rao, Zilin Wang +5
Subband-based approaches process subbands in parallel through the model with shared parameters to learn the commonality of local spectrums for noise reduction. In this way, they ha…
Distance-based Weight Transfer from Near-field to Far-field Speaker Verification
Li Zhang, Qing Wang, Hongji Wang +4
The scarcity of labeled far-field speech is a constraint for training superior far-field speaker verification systems. Fine-tuning the model pre-trained on large-scale near-field s…
TEA-PSE 3.0: Tencent-Ethereal-Audio-Lab Personalized Speech Enhancement System For ICASSP 2023 DNS Challenge
Yukai Ju, Jun Chen, Shimin Zhang +6
This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- T…
Speech Enhancement with Fullband-Subband Cross-Attention Network
Jun Chen, Wei Rao, Zilin Wang +5
FullSubNet has shown its promising performance on speech enhancement by utilizing both fullband and subband information. However, the relationship between fullband and subband in F…
Speech Enhancement with Intelligent Neural Homomorphic Synthesis
Shulin He, Wei Rao, Jinjiang Liu +5
Most neural network speech enhancement models ignore speech production mathematical models by directly mapping Fourier transform spectrums or waveforms. In this work, we propose a…
spatial-dccrn: dccrn equipped with frame-level angle feature and hybrid filtering for multi-channel speech enhancement
Shubo Lv, Yihui Fu, Yukai Jv +4
Recently, multi-channel speech enhancement has drawn much interest due to the use of spatial information to distinguish target speech from interfering signal. To make full use of s…
Improving Channel Decorrelation for Multi-Channel Target Speech Extraction
Jiangyu Han, Wei Rao, Yannan Wang +1
Target speech extraction has attracted widespread attention. When microphone arrays are available, the additional spatial information can be helpful in extracting the target speech…
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing
Wei Rao, Yihui Fu, Yanxin Hu +11
The ConferencingSpeech 2021 challenge is proposed to stimulate research on far-field multi-channel speech enhancement for video conferencing. The challenge consists of two separate…
Target Speaker Verification with Selective Auditory Attention for Single and Multi-talker Speech
Chenglin Xu, Wei Rao, Jibin Wu +1
Speaker verification has been studied mostly under the single-talker condition. It is adversely affected in the presence of interference speakers. Inspired by the study on target s…
Adversarial Training for Multi-domain Speaker Recognition
Qing Wang, Wei Rao, Pengcheng Guo +1
In real-life applications, the performance of speaker recognition systems always degrades when there is a mismatch between training and evaluation data. Many domain adaptation meth…
HLT-NUS Submission for NIST 2019 Multimedia Speaker Recognition Evaluation
Rohan Kumar Das, Ruijie Tao, Jichen Yang +3
This work describes the speaker verification system developed by Human Language Technology Laboratory, National University of Singapore (HLT-NUS) for 2019 NIST Multimedia Speaker R…
The INTERSPEECH 2020 Far-Field Speaker Verification Challenge
Xiaoyi Qin, Ming Li, Hui Bu +4
The INTERSPEECH 2020 Far-Field Speaker Verification Challenge (FFSVC 2020) addresses three different research problems under well-defined conditions: far-field text-dependent speak…
Time-domain speaker extraction network
Chenglin Xu, Wei Rao, Eng Siong Chng +1
Speaker extraction is to extract a target speaker's voice from multi-talker speech. It simulates humans' cocktail party effect or the selective listening ability. The prior work mo…
SpEx: Multi-Scale Time Domain Speaker Extraction Network
Chenglin Xu, Wei Rao, Eng Siong Chng +1
Speaker extraction aims to mimic humans' selective auditory attention by extracting a target speaker's voice from a multi-talker environment. It is common to perform the extraction…
The FFSVC 2020 Evaluation Plan
Xiaoyi Qin, Ming Li, Hui Bu +4
The Far-Field Speaker Verification Challenge 2020 (FFSVC20) is designed to boost the speaker verification research with special focus on far-field distributed microphone arrays und…
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
Kong Aik Lee, Ville Hautamaki, Tomi Kinnunen +43
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which…
Optimization of Speaker Extraction Neural Network with Magnitude and Temporal Spectrum Approximation Loss
Chenglin Xu, Wei Rao, Eng Siong Chng +1
The SpeakerBeam-FE (SBF) method is proposed for speaker extraction. It attempts to overcome the problem of unknown number of speakers in an audio recording during source separation…
Target Speaker Extraction for Overlapped Multi-Talker Speaker Verification
Wei Rao, Chenglin Xu, Eng Siong Chng +1
The performance of speaker verification degrades significantly when the test speech is corrupted by interference speakers. Speaker diarization does well to separate speakers if the…
Fantastic 4 system for NIST 2015 Language Recognition Evaluation
Kong Aik Lee, Ville Hautamäki, Anthony Larcher +14
This article describes the systems jointly submitted by Institute for Infocomm (IR), the Laboratoire d'Informatique de l'Université du Maine (LIUM), Nanyang Technology Universi…
ISAR Image Formation Using Sequential Minimization of L0 and L2 Norms
Gang Li, Wei Rao, Xiqin Wang +1
A sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging is proposed. Based on the parametric sparse representation of the received ISAR signal, the problem o…