15 citations · 26 across the 4 of their papers we have counts for
5 papers
Speech Separation Based on Multi-Stage Elaborated Dual-Path Deep BiLSTM with Auxiliary Identity Loss
Ziqiang Shi, Rujie Liu, Jiqing Han
Deep neural network with dual-path bi-directional long short-term memory (BiLSTM) block has been proved to be very effective in sequence modeling, especially in speech separation.…
LaFurca: Iterative Refined Speech Separation Based on Context-Aware Dual-Path Parallel Bi-LSTM
Ziqiang Shi, Rujie Liu, Jiqing Han
Deep neural network with dual-path bi-directional long short-term memory (BiLSTM) block has been proved to be very effective in sequence modeling, especially in speech separation,…
FurcaNet: An end-to-end deep gated convolutional, long short-term memory, deep neural networks for single channel speech separation
Ziqiang Shi, Huibin Lin, Liu Liu +4
Deep gated convolutional networks have been proved to be very effective in single channel speech separation. However current state-of-the-art framework often considers training the…
Is CQT more suitable for monaural speech separation than STFT? an empirical study
Ziqiang Shi, Huibin Lin, Liu Liu +2
Short-time Fourier transform (STFT) is used as the front end of many popular successful monaural speech separation methods, such as deep clustering (DPCL), permutation invariant tr…
Guarantees of Augmented Trace Norm Models in Tensor Recovery
Ziqiang Shi, Jiqing Han, Tieran Zheng +2
This paper studies the recovery guarantees of the models of minimizing where is a tensor and a…