10 citations · 32 across the 9 of their papers we have counts for
9 papers
Deep factorization for speech signal
Lantian Li, Dong Wang, Yixiang Chen +3
Various informative factors mixed in speech signals, leading to great difficulty when decoding any of the factors. An intuitive idea is to factorize each speech frame into individu…
AP17-OLR Challenge: Data, Plan, and Baseline
Zhiyuan Tang, Dong Wang, Yixiang Chen +1
We present the data profile and the evaluation plan of the second oriental language recognition (OLR) challenge AP17-OLR. Compared to the event last year (AP16-OLR), the new challe…
Deep Factorization for Speech Signal
Dong Wang, Lantian Li, Ying Shi +2
Speech signals are complex intermingling of various informative factors, and this information blending makes decoding any of the individual factors extremely difficult. A natural i…
Speaker Recognition with Cough, Laugh and "Wei"
Miao Zhang, Yixiang Chen, Lantian Li +1
This paper proposes a speaker recognition (SRE) task with trivial speech events, such as cough and laugh. These trivial events are ubiquitous in conversations and less subjected to…
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…
Phone-aware Neural Language Identification
Zhiyuan Tang, Dong Wang, Yixiang Chen +2
Pure acoustic neural models, particularly the LSTM-RNN model, have shown great potential in language identification (LID). However, the phonetic information has been largely overlo…
Deep Speaker Feature Learning for Text-independent Speaker Verification
Lantian Li, Yixiang Chen, Ying Shi +2
Recently deep neural networks (DNNs) have been used to learn speaker features. However, the quality of the learned features is not sufficiently good, so a complex back-end model, e…
Phonetic Temporal Neural Model for Language Identification
Zhiyuan Tang, Dong Wang, Yixiang Chen +2
Deep neural models, particularly the LSTM-RNN model, have shown great potential for language identification (LID). However, the use of phonetic information has been largely overloo…
Weakly Supervised PLDA Training
Lantian Li, Yixiang Chen, Dong Wang +1
PLDA is a popular normalization approach for the i-vector model, and it has delivered state-of-the-art performance in speaker verification. However, PLDA training requires a large…