Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling-Reference-Cited by-同舟云学术

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Denoispeech: Denoising Text to Speech with Frame-Level Noise Modeling

Published:2021-06-06 Issue: Volume: Page:
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Container-title:ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Zhang Chen,Ren Yi,Tan Xu,Liu Jinglin,Zhang Kejun,Qin Tao,Zhao Sheng,Liu Tie-Yan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9413349/9413350/09413934.pdf?arnumber=9413934

Cited by 22 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. DeepMine-Multi-TTS: A Persian Speech Corpus for Multi-Speaker Text-to-Speech;2024-08-19

2. NRAdapt: Noise-Robust Adaptive Text to Speech Using Untranscribed Data;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Noise-Robust Zero-Shot Text-to-Speech Synthesis Conditioned on Self-Supervised Speech-Representation Model with Adapters;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. An Experimental Comparison of Noise-Robust Text-To-Speech Synthesis Systems Based On Self-Supervised Representation;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

5. HAEPF: hybrid approach for estimating pitch frequency in the presence of reverberation;Multimedia Tools and Applications;2024-02-24

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