13 citations · 40 across the 10 of their papers we have counts for
10 papers
NeuralMAG: Fast and Generalizable Micromagnetic Simulation with Deep Neural Nets
Yunqi Cai, Jiangnan Li, Dong Wang
Micromagnetics has made significant strides, particularly due to its wide-ranging applications in magnetic storage design. Numerical simulation is a cornerstone of micromagnetics r…
An MAP Estimation for Between-Class Variance
Jiao Han, Yunqi Cai, Lantian Li +2
Probabilistic linear discriminant analysis (PLDA) has been widely used in open-set verification tasks, such as speaker verification. A potential issue of this model is that the tra…
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…
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…
Deep generative factorization for speech signal
Haoran Sun, Lantian Li, Yunqi Cai +3
Various information factors are blended in speech signals, which forms the primary difficulty for most speech information processing tasks. An intuitive idea is to factorize speech…
Domain-Invariant Speaker Vector Projection by Model-Agnostic Meta-Learning
Jiawen Kang, Ruiqi Liu, Lantian Li +3
Domain generalization remains a critical problem for speaker recognition, even with the state-of-the-art architectures based on deep neural nets. For example, a model trained on re…
Deep Normalization for Speaker Vectors
Yunqi Cai, Lantian Li, Dong Wang +1
Deep speaker embedding has demonstrated state-of-the-art performance in speaker recognition tasks. However, one potential issue with this approach is that the speaker vectors deriv…
CN-CELEB: a challenging Chinese speaker recognition dataset
Yue Fan, Jiawen Kang, Lantian Li +7
Recently, researchers set an ambitious goal of conducting speaker recognition in unconstrained conditions where the variations on ambient, channel and emotion could be arbitrary. H…
On Investigation of Unsupervised Speech Factorization Based on Normalization Flow
Haoran Sun, Yunqi Cai, Lantian Li +1
Speech signals are complex composites of various information, including phonetic content, speaker traits, channel effect, etc. Decomposing this complicated mixture into independent…