11 citations · 21 across the 17 of their papers we have counts for
7 papers · 1 filter
Leveraging In-the-Wild Data for Effective Self-Supervised Pretraining in Speaker Recognition
Shuai Wang, Qibing Bai, Qi Liu +5
Current speaker recognition systems primarily rely on supervised approaches, constrained by the scale of labeled datasets. To boost the system performance, researchers leverage lar…
Attention-based Encoder-Decoder End-to-End Neural Diarization with Embedding Enhancer
Zhengyang Chen, Bing Han, Shuai Wang +1
Deep neural network-based systems have significantly improved the performance of speaker diarization tasks. However, end-to-end neural diarization (EEND) systems often struggle to…
InstructME: An Instruction Guided Music Edit And Remix Framework with Latent Diffusion Models
Bing Han, Junyu Dai, Weituo Hao +6
Music editing primarily entails the modification of instrument tracks or remixing in the whole, which offers a novel reinterpretation of the original piece through a series of oper…
Exploring Binary Classification Loss For Speaker Verification
Bing Han, Zhengyang Chen, Yanmin Qian
The mismatch between close-set training and open-set testing usually leads to significant performance degradation for speaker verification task. For existing loss functions, metric…
Wespeaker baselines for VoxSRC2023
Shuai Wang, Chengdong Liang, Xu Xiang +4
This report showcases the results achieved using the wespeaker toolkit for the VoxSRC2023 Challenge. Our aim is to provide participants, especially those with limited experience, w…
Attention-based Encoder-Decoder Network for End-to-End Neural Speaker Diarization with Target Speaker Attractor
Zhengyang Chen, Bing Han, Shuai Wang +1
This paper proposes a novel Attention-based Encoder-Decoder network for End-to-End Neural speaker Diarization (AED-EEND). In AED-EEND system, we incorporate the target speaker enro…
Self-Supervised Learning with Cluster-Aware-DINO for High-Performance Robust Speaker Verification
Bing Han, Zhengyang Chen, Yanmin Qian
Automatic speaker verification task has made great achievements using deep learning approaches with the large-scale manually annotated dataset. However, it's very difficult and exp…