IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System

V. Panayotov, G. Chen, D. Povey, and S. Khudanpur, “Librispeech: an asr corpus based on public domain audio books,” in 2015 IEEE international conference on acoustics, speech and signal processing (ICASSP) . IEEE, 2015, pp. 5206–5210

2015

Earlier work this paper cites.

A. Van Den Oord, O. Vinyals et al. , “Neural discrete representation learning,” Advances in neural information processing systems , vol. 30, 2017

2017

Earlier work this paper cites.

H. Bu, J. Du, X. Na, B. Wu, and H. Zheng, “Aishell-1: An open-source mandarin speech corpus and a speech recognition baseline,” in 2017 20th conference of the oriental chapter of the international coordinating committee on speech databases and speech I/O systems and assessment (O-COCOSDA) . IEEE, 2017, pp. 1–5

2017

Earlier work this paper cites.

A. Défossez, N. Usunier, L. Bottou, and F. Bach, “Demucs: Deep extractor for music sources with extra unlabeled data remixed,” arXiv preprint arXiv:1909.01174 , 2019

Original

2019

Earlier work this paper cites.

R. Ardila, M. Branson, K. Davis, M. Henretty, M. Kohler, J. Meyer, R. Morais, L. Saunders, F. M. Tyers, and G. Weber, “Common voice: A massively-multilingual speech corpus,” arXiv preprint arXiv:1912.06670 , 2019

Original

2019

Earlier work this paper cites.

J. Kong, J. Kim, and J. Bae, “Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,” Advances in neural information processing systems , vol. 33, pp. 17 022–17 033, 2020

2020

Earlier work this paper cites.

E. Casanova, J. Weber, C. D. Shulby, A. C. Junior, E. Gölge, and M. A. Ponti, “Yourtts: Towards zero-shot multi-speaker tts and zero-shot voice conversion for everyone,” in International Conference on Machine Learning . PMLR, 2022, pp. 2709–2720

2022

Earlier work this paper cites.

S.-g. Lee, W. Ping, B. Ginsburg, B. Catanzaro, and S. Yoon, “Bigvgan: A universal neural vocoder with large-scale training,” arXiv preprint arXiv:2206.04658 , 2022

Original

2022

Earlier work this paper cites.

Z. Gao, S. Zhang, I. McLoughlin, and Z. Yan, “Paraformer: Fast and accurate parallel transformer for non-autoregressive end-to-end speech recognition,” arXiv preprint arXiv:2206.08317 , 2022

Original

2022

Cited alongside, same era.

Z. Jiang, J. Liu, Y. Ren, J. He, C. Zhang, Z. Ye, P. Wei, C. Wang, X. Yin, Z. Ma et al. , “Mega-tts 2: Zero-shot text-to-speech with arbitrary length speech prompts,” arXiv preprint arXiv:2307.07218 , 2023

Original

2023

Cited alongside, same era.

C. Wang, S. Chen, Y. Wu, Z. Zhang, L. Zhou, S. Liu, Z. Chen, Y. Liu, H. Wang, J. Li et al. , “Neural codec language models are zero-shot text to speech synthesizers,” arXiv preprint arXiv:2301.02111 , 2023

Original

2023

Cited alongside, same era.

J. Betker, “Better speech synthesis through scaling,” arXiv preprint arXiv:2305.07243 , 2023

Original

2023

Cited alongside, same era.

S. Liao, Y. Wang, T. Li, Y. Cheng, R. Zhang, R. Zhou, and Y. Xing, “Fish-speech: Leveraging large language models for advanced multilingual text-to-speech synthesis,” arXiv preprint arXiv:2411.01156 , 2024

Original

2024

Later among the works it cites.

Z. Du, Q. Chen, S. Zhang, K. Hu, H. Lu, Y. Yang, H. Hu, S. Zheng, Y. Gu, Z. Ma et al. , “Cosyvoice: A scalable multilingual zero-shot text-to-speech synthesizer based on supervised semantic tokens,” arXiv preprint arXiv:2407.05407 , 2024

Original

2024

Later among the works it cites.

H.-H. Guo, K. Liu, F.-Y. Shen, Y.-C. Wu, F.-L. Xie, K. Xie, and K.-T. Xu, “Fireredtts: A foundation text-to-speech framework for industry-level generative speech applications,” arXiv preprint arXiv:2409.03283 , 2024

Original

2024

Later among the works it cites.

Y. Chen, Z. Niu, Z. Ma, K. Deng, C. Wang, J. Zhao, K. Yu, and X. Chen, “F5-tts: A fairytaler that fakes fluent and faithful speech with flow matching,” arXiv preprint arXiv:2410.06885 , 2024

Original

2024

Later among the works it cites.