activity
20222025
most citedSelf-Supervised Learning with Cluster-Aware-DINO for High-Performance Robust Speaker Verification

4 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

eess.IV2025

TCM-Tongue: A Standardized Tongue Image Dataset with Pathological Annotations for AI-Assisted TCM Diagnosis

Xuebo Jin, Longfei Gao, Anshuo Tong +7

Traditional Chinese medicine (TCM) tongue diagnosis, while clinically valuable, faces standardization challenges due to subjective interpretation and inconsistent imaging protocols…

cs.SD2024

Generating Speakers by Prompting Listener Impressions for Pre-trained Multi-Speaker Text-to-Speech Systems

Zhengyang Chen, Xuechen Liu, Erica Cooper +2

This paper proposes a speech synthesis system that allows users to specify and control the acoustic characteristics of a speaker by means of prompts describing the speaker's traits…

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

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…

cs.SD20231 cited

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…

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…