79 citations · 167 across the 9 of their papers we have counts for
12 papers
Speech Separation with Pretrained Frontend to Minimize Domain Mismatch
Wupeng Wang, Zexu Pan, Xinke Li +2
Speech separation seeks to separate individual speech signals from a speech mixture. Typically, most separation models are trained on synthetic data due to the unavailability of ta…
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…
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…
Self-Supervised Learning Based Domain Adaptation for Robust Speaker Verification
Zhengyang Chen, Shuai Wang, Yanmin Qian
Large performance degradation is often observed for speaker ver-ification systems when applied to a new domain dataset. Givenan unlabeled target-domain dataset, unsupervised domain…
Voice activity detection in the wild: A data-driven approach using teacher-student training
Heinrich Dinkel, Shuai Wang, Xuenan Xu +2
Voice activity detection is an essential pre-processing component for speech-related tasks such as automatic speech recognition (ASR). Traditional supervised VAD systems obtain fra…
Unit selection synthesis based data augmentation for fixed phrase speaker verification
Houjun Huang, Xu Xiang, Fei Zhao +2
Data augmentation is commonly used to help build a robust speaker verification system, especially in limited-resource case. However, conventional data augmentation methods usually…