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20212026
most citedSelf-Supervised Learning Based Domain Adaptation for Robust Speaker Verification

41 citations · 69 across the 18 of their papers we have counts for

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5 papers · 1 filter

eess.AS2024

Prototype and Instance Contrastive Learning for Unsupervised Domain Adaptation in Speaker Verification

Wen Huang, Bing Han, Zhengyang Chen +2

Speaker verification system trained on one domain usually suffers performance degradation when applied to another domain. To address this challenge, researchers commonly use featur…

eess.AS20241 cited

Target Speech Diarization with Multimodal Prompts

Yidi Jiang, Ruijie Tao, Zhengyang Chen +2

Traditional speaker diarization seeks to detect ``who spoke when'' according to speaker characteristics. Extending to target speech diarization, we detect ``when target event occur…

eess.AS2023

Prompt-driven Target Speech Diarization

Yidi Jiang, Zhengyang Chen, Ruijie Tao +3

We introduce a novel task named `target speech diarization', which seeks to determine `when target event occurred' within an audio signal. We devise a neural architecture called Pr…

eess.AS2023

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…

eess.AS2023

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…