Disentangling Correlated Speaker and Noise for Speech Synthesis via Data Augmentation and Adversarial Factorization-Reference-Cited by-同舟云学术

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Disentangling Correlated Speaker and Noise for Speech Synthesis via Data Augmentation and Adversarial Factorization

Published:2019-05 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Hsu Wei-Ning,Zhang Yu,Weiss Ron J.,Chung Yu-An,Wang Yuxuan,Wu Yonghui,Glass James

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8671773/8682151/08683561.pdf?arnumber=8683561

Cited by 65 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 voice conversion using adversarial training with multi-feature decoupling;Engineering Applications of Artificial Intelligence;2024-05

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. A Voice Cloning Model for Rhythm and Content De-Entanglement;Artificial Intelligence and Robotics Research;2024

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