41 citations · 104 across the 27 of their papers we have counts for
8 papers · 1 filter
A comprehensive study on self-supervised distillation for speaker representation learning
Zhengyang Chen, Yao Qian, Bing Han +2
In real application scenarios, it is often challenging to obtain a large amount of labeled data for speaker representation learning due to speaker privacy concerns. Self-supervised…
Build a SRE Challenge System: Lessons from VoxSRC 2022 and CNSRC 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
Many speaker recognition challenges have been held to assess the speaker verification system in the wild and probe the performance limit. Voxceleb Speaker Recognition Challenge (Vo…
Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit
Hongji Wang, Chengdong Liang, Shuai Wang +5
Speaker modeling is essential for many related tasks, such as speaker recognition and speaker diarization. The dominant modeling approach is fixed-dimensional vector representation…
SJTU-AISPEECH System for VoxCeleb Speaker Recognition Challenge 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
This report describes the SJTU-AISPEECH system for the Voxceleb Speaker Recognition Challenge 2022. For track1, we implemented two kinds of systems, the online system and the offli…
The SJTU System for Short-duration Speaker Verification Challenge 2021
Bing Han, Zhengyang Chen, Zhikai Zhou +1
This paper presents the SJTU system for both text-dependent and text-independent tasks in short-duration speaker verification (SdSV) challenge 2021. In this challenge, we explored…
Self-Supervised Speaker Verification Using Dynamic Loss-Gate and Label Correction
Bing Han, Zhengyang Chen, Yanmin Qian
For self-supervised speaker verification, the quality of pseudo labels decides the upper bound of the system due to the massive unreliable labels. In this work, we propose dynamic…
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action Recognition
Zhan Chen, Hong Liu, Tianyu Guo +3
Self-supervised skeleton-based action recognition with contrastive learning has attracted much attention. Recent literature shows that data augmentation and large sets of contrasti…
The SJTU X-LANCE Lab System for CNSRC 2022
Zhengyang Chen, Bei Liu, Bing Han +2
This technical report describes the SJTU X-LANCE Lab system for the three tracks in CNSRC 2022. In this challenge, we explored the speaker embedding modeling ability of deep ResNet…