5 citations · 25 across the 24 of their papers we have counts for
13 papers · 1 filter
Speech Token Prediction via Compressed-to-fine Language Modeling for Speech Generation
Wenrui Liu, Qian Chen, Wen Wang +11
Neural audio codecs, used as speech tokenizers, have demonstrated remarkable potential in the field of speech generation. However, to ensure high-fidelity audio reconstruction, neu…
Pushing the Frontiers of Self-Distillation Prototypes Network with Dimension Regularization and Score Normalization
Yafeng Chen, Chong Deng, Hui Wang +4
Developing robust speaker verification (SV) systems without speaker labels has been a longstanding challenge. Earlier research has highlighted a considerable performance gap betwee…
Exploring Text-Queried Sound Event Detection with Audio Source Separation
Han Yin, Jisheng Bai, Yang Xiao +6
In sound event detection (SED), overlapping sound events pose a significant challenge, as certain events can be easily masked by background noise or other events, resulting in poor…
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision
Yafeng Chen, Siqi Zheng, Hui Wang +4
Training speaker-discriminative and robust speaker verification systems without explicit speaker labels remains a persisting challenge. In this paper, we propose a new self-supervi…
ERes2NetV2: Boosting Short-Duration Speaker Verification Performance with Computational Efficiency
Yafeng Chen, Siqi Zheng, Hui Wang +4
Speaker verification systems experience significant performance degradation when tasked with short-duration trial recordings. To address this challenge, a multi-scale feature fusio…
3D-Speaker-Toolkit: An Open-Source Toolkit for Multimodal Speaker Verification and Diarization
Yafeng Chen, Siqi Zheng, Hui Wang +8
We introduce 3D-Speaker-Toolkit, an open-source toolkit for multimodal speaker verification and diarization, designed for meeting the needs of academic researchers and industrial p…
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision
Yafeng Chen, Siqi Zheng, Hui Wang +5
Training speaker-discriminative and robust speaker verification systems without explicit speaker labels remains a persistent challenge. In this paper, we propose a novel self-super…
An Enhanced Res2Net with Local and Global Feature Fusion for Speaker Verification
Yafeng Chen, Siqi Zheng, Hui Wang +3
Effective fusion of multi-scale features is crucial for improving speaker verification performance. While most existing methods aggregate multi-scale features in a layer-wise manne…
Pushing the limits of self-supervised speaker verification using regularized distillation framework
Yafeng Chen, Siqi Zheng, Hui Wang +2
Training robust speaker verification systems without speaker labels has long been a challenging task. Previous studies observed a large performance gap between self-supervised and…
Graph Convolutional Network Based Semi-Supervised Learning on Multi-Speaker Meeting Data
Fuchuan Tong, Siqi Zheng, Min Zhang +4
Unsupervised clustering on speakers is becoming increasingly important for its potential uses in semi-supervised learning. In reality, we are often presented with enormous amounts…
Improved Meta-Learning Training for Speaker Verification
Yafeng Chen, Wu Guo, Bin Gu
Meta-learning has recently become a research hotspot in speaker verification (SV). We introduce two methods to improve the meta-learning training for SV in this paper. For the firs…
Multi-task Metric Learning for Text-independent Speaker Verification
Yafeng Chen, Wu Guo, Jingjing Shi +2
In this work, we introduce metric learning (ML) to enhance the deep embedding learning for text-independent speaker verification (SV). Specifically, the deep speaker embedding netw…
Exploring Universal Speech Attributes for Speaker Verification with an Improved Cross-stitch Network
Jiajun Qi, Wu Guo, Jingjing Shi +2
The universal speech attributes for x-vector based speaker verification (SV) are addressed in this paper. The manner and place of articulation form the fundamental speech attribute…