Learning Expressive Disentangled Speech Representations with Soft Speech Units and Adversarial Style Augmentation
Author:
Affiliation:
1. Ping An Technology (Shenzhen) Co., Ltd.,China
Funder
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650293.pdf?arnumber=10650293
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1. Autovc: Zero-shot voice style transfer with only autoencoder loss;Qian
2. One-Shot Voice Conversion by Vector Quantization
3. VQVC+: One-Shot Voice Conversion by Vector Quantization and U-Net Architecture
4. Avqvc: One-Shot Voice Conversion By Vector Quantization With Applying Contrastive Learning
5. CLN-VC: Text-Free Voice Conversion Based on Fine-Grained Style Control and Contrastive Learning with Negative Samples Augmentation
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1. EAD-VC: Enhancing Speech Auto-Disentanglement for Voice Conversion with IFUB Estimator and Joint Text-Guided Consistent Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
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