most citedExploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech

10 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2022

Label-free Knowledge Distillation with Contrastive Loss for Light-weight Speaker Recognition

Zhiyuan Peng, Xuanji He, Ke Ding +2

Very deep models for speaker recognition (SR) have demonstrated remarkable performance improvement in recent research. However, it is impractical to deploy these models for on-devi…

cs.SD2022

Covariance Regularization for Probabilistic Linear Discriminant Analysis

Zhiyuan Peng, Mingjie Shao, Xuanji He +4

Probabilistic linear discriminant analysis (PLDA) is commonly used in speaker verification systems to score the similarity of speaker embeddings. Recent studies improved the perfor…

eess.AS20221 cited

Convolution-Based Channel-Frequency Attention for Text-Independent Speaker Verification

Jingyu Li, Yusheng Tian, Tan Lee

Deep convolutional neural networks (CNNs) have been applied to extracting speaker embeddings with significant success in speaker verification. Incorporating the attention mechanism…

cs.SD2022

Unifying Cosine and PLDA Back-ends for Speaker Verification

Zhiyuan Peng, Xuanji He, Ke Ding +2

State-of-art speaker verification (SV) systems use a back-end model to score the similarity of speaker embeddings extracted from a neural network model. The commonly used back-end…

eess.AS202110 cited

Exploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech

Ying Qin, Wei Liu, Zhiyuan Peng +4

Alzheimer's disease (AD) is a progressive neurodegenerative disease and recently attracts extensive attention worldwide. Speech technology is considered a promising solution for th…