41 citations · 67 across the 13 of their papers we have counts for
13 papers
The Impact of Silence on Speech Anti-Spoofing
Yuxiang Zhang, Zhuo Li, Jingze Lu +3
The current speech anti-spoofing countermeasures (CMs) show excellent performance on specific datasets. However, removing the silence of test speech through Voice Activity Detectio…
Underwater Acoustic Target Recognition based on Smoothness-inducing Regularization and Spectrogram-based Data Augmentation
Ji Xu, Yuan Xie, Wenchao Wang
Underwater acoustic target recognition is a challenging task owing to the intricate underwater environments and limited data availability. Insufficient data can hinder the ability…
Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification
Zhuo Li, Jingze Lu, Zhenduo Zhao +2
Utilizing the large-scale unlabeled data from the target domain via pseudo-label clustering algorithms is an important approach for addressing domain adaptation problems in speaker…
The HCCL system for VoxCeleb Speaker Recognition Challenge 2022
Zhenduo Zhao, Zhuo Li, Wenchao Wang +1
This report describes our submission to track1 and track3 for VoxCeleb Speaker Recognition Challenge 2022(VoxSRC2022). Our best system achieves minDCF 0.1397 and EER 2.414 in track…
PCF: ECAPA-TDNN with Progressive Channel Fusion for Speaker Verification
Zhenduo Zhao, Zhuo Li, Wenchao Wang +1
ECAPA-TDNN is currently the most popular TDNN-series model for speaker verification, which refreshed the state-of-the-art(SOTA) performance of TDNN models. However, one-dimensional…
Deepfake Detection System for the ADD Challenge Track 3.2 Based on Score Fusion
Yuxiang Zhang, Jingze Lu, Xingming Wang +5
This paper describes the deepfake audio detection system submitted to the Audio Deep Synthesis Detection (ADD) Challenge Track 3.2 and gives an analysis of score fusion. The propos…
The HCCL System for the NIST SRE21
Zhuo Li, Runqiu Xiao, Hangting Chen +3
This paper describes the systems developed by the HCCL team for the NIST 2021 speaker recognition evaluation (NIST SRE21).We first explore various state-of-the-art speaker embeddin…
SASV Based on Pre-trained ASV System and Integrated Scoring Module
Yuxiang Zhang, Zhuo Li, Wenchao Wang +1
Based on the assumption that there is a correlation between anti-spoofing and speaker verification, a Total-Divide-Total integrated Spoofing-Aware Speaker Verification (SASV) syste…
Back-ends Selection for Deep Speaker Embeddings
Zhuo Li, Runqiu Xiao, Zihan Zhang +3
Probabilistic Linear Discriminant Analysis (PLDA) was the dominant and necessary back-end for early speaker recognition approaches, like i-vector and x-vector. However, with the de…
The HCCL Speaker Verification System for Far-Field Speaker Verification Challenge
Zhuo Li, Ce Fang, Runqiu Xiao +3
This paper describes the systems submitted by team HCCL to the Far-Field Speaker Verification Challenge. Our previous work in the AIshell Speaker Verification Challenge 2019 shows…
Adaptive Margin Circle Loss for Speaker Verification
Runqiu Xiao
Deep-Neural-Network (DNN) based speaker verification sys-tems use the angular softmax loss with margin penalties toenhance the intra-class compactness of speaker embeddings,which a…
Parsimonious HMMs for Offline Handwritten Chinese Text Recognition
Wenchao Wang, Jun Du, Zi-Rui Wang
Recently, hidden Markov models (HMMs) have achieved promising results for offline handwritten Chinese text recognition. However, due to the large vocabulary of Chinese characters w…
DenseRAN for Offline Handwritten Chinese Character Recognition
Wenchao Wang, Jianshu Zhang, Jun Du +2
Recently, great success has been achieved in offline handwritten Chinese character recognition by using deep learning methods. Chinese characters are mainly logographic and consist…