Disentangling Style and Speaker Attributes for TTS Style Transfer

Disentangling Style and Speaker Attributes for TTS Style Transfer

24 January 2022

Lei Xie

Papers citing "Disentangling Style and Speaker Attributes for TTS Style Transfer"

6 / 6 papers shown

Title
Exploring synthetic data for cross-speaker style transfer in style representation based TTS Lucas Ueda Leonardo B. de M. M. Marques Flávio O. Simões Mário Uliani Neto Fernando Runstein Bianca Dal Bó Paula D. P. Costa 21 0 0 25 Sep 2024
DiCLET-TTS: Diffusion Model based Cross-lingual Emotion Transfer for Text-to-Speech -- A Study between English and Mandarin Tao Li Chenxu Hu Jian Cong Xinfa Zhu Jingbei Li Qiao Tian Yuping Wang Linfu Xie DiffM 17 8 0 02 Sep 2023
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre Guangyan Zhang Ying Qin W. Zhang Jialun Wu Mei Li Yu Gai Feijun Jiang Tan Lee 40 26 0 29 Jun 2022
VoxCeleb2: Deep Speaker Recognition Joon Son Chung Arsha Nagrani Andrew Zisserman 214 2,224 0 14 Jun 2018
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis Ye Jia Yu Zhang Ron J. Weiss Quan Wang Jonathan Shen ... Z. Chen Patrick Nguyen Ruoming Pang Ignacio López Moreno Yonghui Wu 204 819 0 12 Jun 2018
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,724 0 26 Sep 2016