111 citations · 389 across the 65 of their papers we have counts for
13 papers · 1 filter
A Principle Solution for Enroll-Test Mismatch in Speaker Recognition
Lantian Li, Dong Wang, Jiawen Kang +4
Mismatch between enrollment and test conditions causes serious performance degradation on speaker recognition systems. This paper presents a statistics decomposition (SD) approach…
CN-Celeb: multi-genre speaker recognition
Lantian Li, Ruiqi Liu, Jiawen Kang +6
Research on speaker recognition is extending to address the vulnerability in the wild conditions, among which genre mismatch is perhaps the most challenging, for instance, enrollme…
Can We Trust Deep Speech Prior?
Ying Shi, Haolin Chen, Zhiyuan Tang +3
Recently, speech enhancement (SE) based on deep speech prior has attracted much attention, such as the variational auto-encoder with non-negative matrix factorization (VAE-NMF) arc…
Deep Speaker Vector Normalization with Maximum Gaussianality Training
Yunqi Cai, Lantian Li, Dong Wang +1
Deep speaker embedding represents the state-of-the-art technique for speaker recognition. A key problem with this approach is that the resulting deep speaker vectors tend to be irr…
Deep generative LDA
Yunqi Cai, Dong Wang
Linear discriminant analysis (LDA) is a popular tool for classification and dimension reduction. Limited by its linear form and the underlying Gaussian assumption, however, LDA is…
Remarks on Optimal Scores for Speaker Recognition
Dong Wang
In this article, we first establish the theory of optimal scores for speaker recognition. Our analysis shows that the minimum Bayes risk (MBR) decisions for both the speaker identi…