NVC-Net: End-To-End Adversarial Voice Conversion
Author:
Affiliation:
1. Stuttgart Laboratory 1,Sony Europe B.V. R&D Center
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747020.pdf?arnumber=9747020
Reference30 articles.
1. Accelerating t-SNE using tree-based algorithms;van der maaten;The Journal of Machine Learning Research,2014
2. StarGAN-VC: non-parallel many-to-many Voice Conversion Using Star Generative Adversarial Networks
3. Parallel-data-free voice conversion using cycle-consistent adversarial networks;kaneko,2017
4. StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
5. Starganv2-vc: A diverse, unsupervised, non-parallel framework for natural-sounding voice conversion;aaron li,2021
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