Face-StyleSpeech: Enhancing Zero-shot Speech Synthesis from Face Images with Improved Face-to-Speech Mapping

J. S. Chung and A. Zisserman, “Out of time: Automated lip sync in the wild,” in ACCV 2016 Workshops , ser. Lecture Notes in Computer Science, 2016

2016

Earlier work this paper cites.

A. Nagrani, J. S. Chung, and A. Zisserman, “Voxceleb: A large-scale speaker identification dataset,” in Interspeech , 2017

2017

Earlier work this paper cites.

A. van den Oord, O. Vinyals, and K. Kavukcuoglu, “Neural discrete representation learning,” in NeurIPS , 2017

2017

Earlier work this paper cites.

J. S. Chung, A. W. Senior, O. Vinyals, and A. Zisserman, “Lip reading sentences in the wild,” in CVPR , 2017

2017

Earlier work this paper cites.

S. Arik, J. Chen, K. Peng, W. Ping, and Y. Zhou, “Neural voice cloning with a few samples,” NeurIPS , 2018

2018

Earlier work this paper cites.

J. S. Chung, A. Nagrani, and A. Zisserman, “Voxceleb2: Deep speaker recognition,” in Interspeech , 2018

2018

Earlier work this paper cites.

S. Goto, K. Onishi, Y. Saito, K. Tachibana, and K. Mori, “Face2speech: Towards multi-speaker text-to-speech synthesis using an embedding vector predicted from a face image,” in Interspeech , 2020. [Online]. Available: https://doi.org/10.21437/Interspeech.2020-2136

2020

Earlier work this paper cites.

J. Kong, J. Kim, and J. Bae, “Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,” in NeurIPS , 2020

2020

Earlier work this paper cites.

D. Min, D. B. Lee, E. Yang, and S. J. Hwang, “Meta-stylespeech : Multi-speaker adaptive text-to-speech generation,” in ICML , 2021

2021

Cited alongside, same era.

Y. Ren, C. Hu, X. Tan, T. Qin, S. Zhao, Z. Zhao, and T. Liu, “Fastspeech 2: Fast and high-quality end-to-end text to speech,” in ICLR , 2021

2021

Cited alongside, same era.

A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, G. Krueger, and I. Sutskever, “Learning transferable visual models from natural language supervision,” in ICML , 2021

2021

Cited alongside, same era.

V. Popov, I. Vovk, V. Gogoryan, T. Sadekova, and M. A. Kudinov, “Grad-tts: A diffusion probabilistic model for text-to-speech,” in ICML , 2021

2021

Cited alongside, same era.

E. Casanova, J. Weber, C. D. Shulby, A. C. Júnior, E. Gölge, and M. A. Ponti, “YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for Everyone,” in ICML , 2022

Y. Ren, M. Lei, Z. Huang, S. Zhang, Q. Chen, Z. Yan, and Z. Zhao, “Prosospeech: Enhancing prosody with quantized vector pre-training in text-to-speech,” in ICASSP , 2022

2022

Later among the works it cites.

M. Kang, D. Min, and S. J. Hwang, “Grad-stylespeech: Any-speaker adaptive text-to-speech synthesis with diffusion models,” in ICASSP 2023 , 2023

2023

Closest in time.

J. Lee, J. Son Chung, and S.-W. Chung, “Imaginary voice: Face-styled diffusion model for text-to-speech,” in ICASSP , 2023

2023

Closest in time.

Z. Jiang, Y. Ren, Z. Ye, J. Liu, C. Zhang, Q. Yang, S. Ji, R. Huang, C. Wang, X. Yin et al. , “Mega-tts: Zero-shot text-to-speech at scale with intrinsic inductive bias,” arXiv preprint arXiv:2306.03509 , 2023

Original

2023

Closest in time.

Y. Koizumi, H. Zen, S. Karita, Y. Ding, K. Yatabe, N. Morioka, M. Bacchiani, Y. Zhang, W. Han, and A. Bapna, “Libritts-r: A restored multi-speaker text-to-speech corpus,” in Interspeech , 2023