Many-to-Many Voice Conversion based Feature Disentanglement using Variational Autoencoder

11 July 2021

Papers citing "Many-to-Many Voice Conversion based Feature Disentanglement using Variational Autoencoder"

7 / 7 papers shown

Title
Memory-Centric Computing: Recent Advances in Processing-in-DRAM O. Mutlu Ataberk Olgun Geraldo F. Oliveira Ismail Emir Yüksel 121 4 0 26 Dec 2024
DSVAE: Interpretable Disentangled Representation for Synthetic Speech Detection Amit Kumar Singh Yadav Kratika Bhagtani Ziyue Xiang Paolo Bestagini Stefano Tubaro Edward J. Delp DRL 68 6 0 06 Apr 2023
Time Domain Adversarial Voice Conversion for ADD 2022 Cheng Wen Tingwei Guo Xi Tan Rui Yan Shuran Zhou Chuandong Xie Wei Zou Xiangang Li 74 4 0 19 Apr 2022
Enhanced exemplar autoencoder with cycle consistency loss in any-to-one voice conversion Weida Liang Lantian Li Wenqiang Du Dong Wang 122 0 0 08 Apr 2022
Enhancing Zero-Shot Many to Many Voice Conversion with Self-Attention VAE Ziang Long Yunling Zheng Meng Yu Jack Xin DRL 63 5 0 30 Mar 2022
Training Robust Zero-Shot Voice Conversion Models with Self-supervised Features Trung D. Q. Dang Dung T. Tran Peter Chin K. Koishida SSL 69 15 0 08 Dec 2021
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme Vadim Popov Ivan Vovk Vladimir Gogoryan Tasnima Sadekova Mikhail Kudinov Jiansheng Wei DiffM BDL 149 136 0 28 Sep 2021