Fetching the paper…
Reading the bibliography…
Most Zero-shot Multi-speaker TTS (ZS-TTS) systems support only a single language.
P. Gage, “A new algorithm for data compression,” C Users Journal , vol. 12, no. 2, pp. 23–38, 1994
1994
Earlier work this paper cites.
S. Choi, S. Han, D. Kim, and S. Ha, “Attentron: Few-Shot Text-to-Speech Utilizing Attention-Based Variable-Length Embedding,” in Proc. Interspeech 2020 , 2020, pp. 2007–2011
2011
Earlier work this paper cites.
Y. Jia, Y. Zhang, R. Weiss, Q. Wang, J. Shen, F. Ren, P. Nguyen, R. Pang, I. L. Moreno, Y. Wu et al. , “Transfer learning from speaker verification to multispeaker text-to-speech synthesis,” in Advances in neural information processing systems , 2018, pp. 4480–4490
2018
Earlier work this paper cites.
S. Arik, J. Chen, K. Peng, W. Ping, and Y. Zhou, “Neural voice cloning with a few samples,” in Advances in Neural Information Processing Systems , 2018, pp. 10 019–10 029
2018
Earlier work this paper cites.
W. Ping, K. Peng, A. Gibiansky, S. O. Arik, A. Kannan, S. Narang, J. Raiman, and J. Miller, “Deep voice 3: 2000-speaker neural text-to-speech,” in International Conference on Learning Representations , 2018. [Online]. Available: https://openreview.net/forum?id=HJtEm4p6Z
2018
Earlier work this paper cites.
J. Shen, R. Pang, R. J. Weiss, M. Schuster, N. Jaitly, Z. Yang, Z. Chen, Y. Zhang, Y. Wang, R. Skerrv-Ryan et al. , “Natural tts synthesis by conditioning wavenet on mel spectrogram predictions,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 4779–4783
2018
Earlier work this paper cites.
H. Zen, V. Dang, R. Clark, Y. Zhang, R. J. Weiss, Y. Jia, Z. Chen, and Y. Wu, “Libritts: A corpus derived from librispeech for text-to-speech,” Interspeech 2019 , 2019
2019
Earlier work this paper cites.
E. Cooper, C.-I. Lai, Y. Yasuda, F. Fang, X. Wang, N. Chen, and J. Yamagishi, “Zero-shot multi-speaker text-to-speech with state-of-the-art neural speaker embeddings,” in ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2020, pp. 6184–6188
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
J. Kahn, M. Rivière, W. Zheng, E. Kharitonov, Q. Xu, P.-E. Mazaré, J. Karadayi, V. Liptchinsky, R. Collobert, C. Fuegen et al. , “Libri-light: A benchmark for asr with limited or no supervision,” in ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2020, pp. 7669–7673
2020
Earlier work this paper cites.
R. Ardila, M. Branson, K. Davis, M. Kohler, J. Meyer, M. Henretty, R. Morais, L. Saunders, F. Tyers, and G. Weber, “Common voice: A massively-multilingual speech corpus,” in Proceedings of the 12th Language Resources and Evaluation Conference , 2020, pp. 4218–4222
2020
Earlier work this paper cites.
E. Casanova, C. Shulby, E. Gölge, N. M. Müller, F. S. de Oliveira, A. Candido Jr., A. da Silva Soares, S. M. Aluisio, and M. A. Ponti, “SC-GlowTTS: An Efficient Zero-Shot Multi-Speaker Text-To-Speech Model,” in Proc. Interspeech 2021 , 2021, pp. 3645–3649
2021
Cited alongside, same era.
J. Kim, J. Kong, and J. Son, “Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,” in International Conference on Machine Learning . PMLR, 2021, pp. 5530–5540
2021
Cited alongside, same era.
2021
Cited alongside, same era.
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
Cited alongside, same era.
S. Kim, K. J. Shih, R. Badlani, J. F. Santos, E. Bakhturina, M. T. Desta, R. Valle, S. Yoon, and B. Catanzaro, “P-flow: A fast and data-efficient zero-shot tts through speech prompting,” in Thirty-seventh Conference on Neural Information Processing Systems , 2023
2023
Later among the works it cites.
2023
Later among the works it cites.
E. Casanova, C. Shulby, A. Korolev, A. C. Junior, A. da Silva Soares, S. Aluísio, and M. A. Ponti, “ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion,” in Proc. INTERSPEECH 2023 , 2023, pp. 1244–1248
2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Chen, C. Wang, Z. Chen, Y. Wu, S. Liu, Z. Chen, J. Li, N. Kanda, T. Yoshioka, X. Xiao et al. , “Wavlm: Large-scale self-supervised pre-training for full stack speech processing,” IEEE Journal of Selected Topics in Signal Processing , vol. 16, no. 6, pp. 1505–1518, 2022
2022
Cited alongside, same era.
J.-B. Alayrac, J. Donahue, P. Luc, A. Miech, I. Barr, Y. Hasson, K. Lenc, A. Mensch, K. Millican, M. Reynolds et al. , “Flamingo: a visual language model for few-shot learning,” Advances in Neural Information Processing Systems , vol. 35, pp. 23 716–23 736, 2022
2022
Cited alongside, same era.
NLLB Team, M. R. Costa-jussà, J. Cross, O. Çelebi, M. Elbayad, K. Heafield, K. Heffernan, H. Kalbassi, …, and J. Wang, “No language left behind: Scaling human-centered machine translation,” 2022
2022
Cited alongside, same era.
T. Saeki, D. Xin, W. Nakata, T. Koriyama, S. Takamichi, and H. Saruwatari, “Utmos: Utokyo-sarulab system for voicemos challenge 2022,” Interspeech 2022 , 2022
2022
Cited alongside, same era.
A. Radford, J. W. Kim, T. Xu, G. Brockman, C. McLeavey, and I. Sutskever, “Robust speech recognition via large-scale weak supervision,” 2022
2022
Cited alongside, same era.
2023
Cited alongside, same era.
A. Défossez, J. Copet, G. Synnaeve, and Y. Adi, “High fidelity neural audio compression,” Transactions on Machine Learning Research , 2023, featured Certification, Reproducibility Certification. [Online]. Available: https://openreview.net/forum?id=ivCd8z8zR2
2023
Cited alongside, same era.
J. Betker, “Better speech synthesis through scaling,” arXiv preprint arXiv:2305.07243 , 2023
2023
Cited alongside, same era.
2023
Later among the works it cites.
M. Le, A. Vyas, B. Shi, B. Karrer, L. Sari, R. Moritz, M. Williamson, V. Manohar, Y. Adi, J. Mahadeokar et al. , “Voicebox: Text-guided multilingual universal speech generation at scale,” in Thirty-seventh Conference on Neural Information Processing Systems , 2023
2023
Later among the works it cites.
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 Proc. INTERSPEECH 2023 , 2023, pp. 5496–5500
2023
Later among the works it cites.
W. Wang, Y. Song, and S. Jha, “Generalizable Zero-Shot Speaker Adaptive Speech Synthesis with Disentangled Representations,” in Proc. INTERSPEECH 2023 , 2023, pp. 4454–4458
2023
Later among the works it cites.
F. S. Oliveira, E. Casanova, A. C. Junior, A. S. Soares, and A. R. Galvão Filho, “Cml-tts: A multilingual dataset for speech synthesis in low-resource languages,” in Text, Speech, and Dialogue , K. Ekštein, F. Pártl, and M. Konopík, Eds. Cham: Springer Nature Switzerland, 2023, pp. 188–199
2023
Later among the works it cites.
Z. Jiang, J. Liu, Y. Ren, J. He, Z. Ye, S. Ji, Q. Yang, C. Zhang, P. Wei, C. Wang, X. Yin, Z. MA, and Z. Zhao, “Mega-tts 2: Boosting prompting mechanisms for zero-shot speech synthesis,” in The Twelfth International Conference on Learning Representations , 2024. [Online]. Available: https://openreview.net/forum?id=mvMI3N4AvD
2024
Closest in time.
Y. A. Li, C. Han, V. Raghavan, G. Mischler, and N. Mesgarani, “Styletts 2: Towards human-level text-to-speech through style diffusion and adversarial training with large speech language models,” Advances in Neural Information Processing Systems , vol. 36, 2024
2024
Closest in time.