5 citations · 6 across the 6 of their papers we have counts for
7 papers
Investigation of Zero-shot Text-to-Speech Models for Enhancing Short-Utterance Speaker Verification
Yiyang Zhao, Shuai Wang, Guangzhi Sun +4
Short-utterance speaker verification presents significant challenges due to the limited information in brief speech segments, which can undermine accuracy and reliability. Recently…
Low-Rank and Sparse Model Merging for Multi-Lingual Speech Recognition and Translation
Qiuming Zhao, Guangzhi Sun, Chao Zhang
Language diversity presents a significant challenge in speech-to-text (S2T) tasks, such as automatic speech recognition and translation. Traditional multi-lingual multi-task traini…
Whisper-PMFA: Partial Multi-Scale Feature Aggregation for Speaker Verification using Whisper Models
Yiyang Zhao, Shuai Wang, Guangzhi Sun +4
In this paper, Whisper, a large-scale pre-trained model for automatic speech recognition, is proposed to apply to speaker verification. A partial multi-scale feature aggregation (P…
A Joint Noise Disentanglement and Adversarial Training Framework for Robust Speaker Verification
Xujiang Xing, Mingxing Xu, Thomas Fang Zheng
Automatic Speaker Verification (ASV) suffers from performance degradation in noisy conditions. To address this issue, we propose a novel adversarial learning framework that incorpo…
Speaker Adaptation for Quantised End-to-End ASR Models
Qiuming Zhao, Guangzhi Sun, Chao Zhang +2
End-to-end models have shown superior performance for automatic speech recognition (ASR). However, such models are often very large in size and thus challenging to deploy on resour…
SAML: Speaker Adaptive Mixture of LoRA Experts for End-to-End ASR
Qiuming Zhao, Guangzhi Sun, Chao Zhang +2
Mixture-of-experts (MoE) models have achieved excellent results in many tasks. However, conventional MoE models are often very large, making them challenging to deploy on resource-…