Unsupervised Representation Disentanglement using Cross Domain Features and Adversarial Learning in Variational Autoencoder based Voice Conversion

22 January 2020

Papers citing "Unsupervised Representation Disentanglement using Cross Domain Features and Adversarial Learning in Variational Autoencoder based Voice Conversion"

6 / 6 papers shown

Title
Expressive-VC: Highly Expressive Voice Conversion with Attention Fusion of Bottleneck and Perturbation Features Ziqian Ning Qicong Xie Pengcheng Zhu Zhichao Wang Liumeng Xue Jixun Yao Linfu Xie Mengxiao Bi 27 16 0 09 Nov 2022
Non-Parallel Voice Conversion for ASR Augmentation Gary Wang Andrew Rosenberg Bhuvana Ramabhadran Fadi Biadsy Yinghui Huang Jesse Emond P. M. Mengibar 13 2 0 15 Sep 2022
Advancing the dimensionality reduction of speaker embeddings for speaker diarisation: disentangling noise and informing speech activity You Jin Kim Hee-Soo Heo Jee-weon Jung Youngki Kwon Bong-Jin Lee Joon Son Chung 24 3 0 07 Oct 2021
StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversion Yinghao Aaron Li A. Zare N. Mesgarani 19 98 0 21 Jul 2021
An Overview of Voice Conversion and its Challenges: From Statistical Modeling to Deep Learning Berrak Sisman Junichi Yamagishi Simon King Haizhou Li BDL 27 316 0 09 Aug 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 16 58 0 29 Jul 2020