39 citations · 132 across the 28 of their papers we have counts for
5 papers · 1 filter
Full-info Training for Deep Speaker Feature Learning
Lantian Li, Zhiyuan Tang, Dong Wang +1
In recent studies, it has shown that speaker patterns can be learned from very short speech segments (e.g., 0.3 seconds) by a carefully designed convolutional & time-delay deep neu…
Enhanced Neural Machine Translation by Learning from Draft
Aodong Li, Shiyue Zhang, Dong Wang +1
Neural machine translation (NMT) has recently achieved impressive results. A potential problem of the existing NMT algorithm, however, is that the decoding is conducted from left t…
Cross-lingual Speaker Verification with Deep Feature Learning
Lantian Li, Dong Wang, Askar Rozi +1
Existing speaker verification (SV) systems often suffer from performance degradation if there is any language mismatch between model training, speaker enrollment, and test. A major…
Deep Speaker Verification: Do We Need End to End?
Dong Wang, Lantian Li, Zhiyuan Tang +1
End-to-end learning treats the entire system as a whole adaptable black box, which, if sufficient data are available, may learn a system that works very well for the target task. T…
A Study on Replay Attack and Anti-Spoofing for Automatic Speaker Verification
Lantian Li, Yixiang Chen, Dong Wang +1
For practical automatic speaker verification (ASV) systems, replay attack poses a true risk. By replaying a pre-recorded speech signal of the genuine speaker, ASV systems tend to b…