Recurrent Phase Reconstruction Using Estimated Phase Derivatives from Deep Neural Networks
Author:
Funder
RWTH Aachen University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9413349/9413350/09413722.pdf?arnumber=9413722
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Exploring Time and Frequency Domain Loss Functions in Real-Time Speech Enhancement Using an Efficient Neural Network: A Comparative Study;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19
2. Phase Reconstruction in Single Channel Speech Enhancement Based on Phase Gradients and Estimated Clean-Speech Amplitudes;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
3. Unrestricted Global Phase Bias-Aware Single-Channel Speech Enhancement with Conformer-Based Metric Gan;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
4. Low-Latency Neural Speech Phase Prediction Based on Parallel Estimation Architecture and Anti-Wrapping Losses for Speech Generation Tasks;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
5. Beyond Clean Phase: Using Silence-Generating Phase for DNN-Based Speech Enhancement;2023 31st European Signal Processing Conference (EUSIPCO);2023-09-04
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