Name
Title | ||
|---|---|---|
DFBNet: Deep Neural Network based Fixed Beamformer for Multi-channel Speech Separation |
Abstract | ||
|---|---|---|
The deep neural networks (DNNs) based beamformers have achieved significant improvements in speech separation tasks. This paper proposes a novel deep neural network (DNN) based fixed beamformer (DFBNet) that uniformly samples the space as a learning module. In addition, the initial coefficients of fixed beamformers in DFBNet are determined by the existing superdirective beamformer. Furthermore, to... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SiPS52927.2021.00042 | 2021 IEEE Workshop on Signal Processing Systems (SiPS) |
Keywords | DocType | ISSN |
multi-channel speech separation,deep neural network,fixed beamformer | Conference | 1520-6130 |
ISBN | Citations | PageRank |
978-1-6654-0144-9 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruqiao Liu | 1 | 0 | 0.34 |
| Yi Zhou | 2 | 15 | 9.83 |
| Hongqing Liu | 3 | 45 | 28.77 |
| Xinmeng Xu | 4 | 0 | 0.34 |
| Jie Jia | 5 | 0 | 1.35 |
| Binbin Chen | 6 | 240 | 31.18 |