39 citations · 132 across the 28 of their papers we have counts for
13 papers · 1 filter
How Speech is Recognized to Be Emotional - A Study Based on Information Decomposition
Haoran Sun, Lantian Li, Thomas Fang Zheng +1
The way that humans encode their emotion into speech signals is complex. For instance, an angry man may increase his pitch and speaking rate, and use impolite words. In this paper,…
A Multi-Resolution Front-End for End-to-End Speech Anti-Spoofing
Wei Liu, Meng Sun, Xiongwei Zhang +2
The choice of an optimal time-frequency resolution is usually a difficult but important step in tasks involving speech signal classification, e.g., speech anti-spoofing. The variat…
Attack on practical speaker verification system using universal adversarial perturbations
Weiyi Zhang, Shuning Zhao, Le Liu +4
In authentication scenarios, applications of practical speaker verification systems usually require a person to read a dynamic authentication text. Previous studies played an audio…
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…
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…
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…
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…
Decision Making Based on Cohort Scores for Speaker Verification
Lantian Li, Renyu Wang, Gang Wang +2
Decision making is an important component in a speaker verification system. For the conventional GMM-UBM architecture, the decision is usually conducted based on the log likelihood…
Max-margin Metric Learning for Speaker Recognition
Lantian Li, Dong Wang, Chao Xing +1
Probabilistic linear discriminant analysis (PLDA) is a popular normalization approach for the i-vector model, and has delivered state-of-the-art performance in speaker recognition.…
Binary Speaker Embedding
Lantian Li, Dong Wang, Chao Xing +2
The popular i-vector model represents speakers as low-dimensional continuous vectors (i-vectors), and hence it is a way of continuous speaker embedding. In this paper, we investiga…