14 citations · 108 across the 30 of their papers we have counts for
14 papers · 1 filter
Enhanced exemplar autoencoder with cycle consistency loss in any-to-one voice conversion
Weida Liang, Lantian Li, Wenqiang Du +1
Recent research showed that an autoencoder trained with speech of a single speaker, called exemplar autoencoder (eAE), can be used for any-to-one voice conversion (VC). Compared to…
Real Additive Margin Softmax for Speaker Verification
Lantian Li, Ruiqian Nai, Dong Wang
The additive margin softmax (AM-Softmax) loss has delivered remarkable performance in speaker verification. A supposed behavior of AM-Softmax is that it can shrink within-class var…
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…
Squeezing value of cross-domain labels: a decoupled scoring approach for speaker verification
Lantian Li, Yang Zhang, Jiawen Kang +2
Domain mismatch often occurs in real applications and causes serious performance reduction on speaker verification systems. The common wisdom is to collect cross-domain data and tr…
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…