8 citations · 10 across the 4 of their papers we have counts for
7 papers
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…
Phonetic-attention scoring for deep speaker features in speaker verification
Lantian Li, Zhiyuan Tang, Ying Shi +1
Recent studies have shown that frame-level deep speaker features can be derived from a deep neural network with the training target set to discriminate speakers by a short speech s…
Gaussian-Constrained training for speaker verification
Lantian Li, Zhiyuan Tang, Ying Shi +1
Neural models, in particular the d-vector and x-vector architectures, have produced state-of-the-art performance on many speaker verification tasks. However, two potential problems…
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…
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…
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…