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Recent prompt-based text-to-speech (TTS) models can clone an unseen speaker using only a short speech prompt.
2017
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2020
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P. S. H. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W. Yih, T. Rocktäschel, S. Riedel, and D. Kiela, “Retrieval-augmented generation for knowledge-intensive NLP tasks,” in Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual , H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, Eds., 2020. [Online]. Available: https://proceedings.neurips.cc/paper/2020/hash/6b493230205f780e1bc26945df7481e5-Abstract.html
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K. Guu, K. Lee, Z. Tung, P. Pasupat, and M. Chang, “Retrieval augmented language model pre-training,” in Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event , ser. Proceedings of Machine Learning Research, vol. 119. PMLR, 2020, pp. 3929–3938. [Online]. Available: http://proceedings.mlr.press/v119/guu20a.html
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2021
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W. Hsu, B. Bolte, Y. H. Tsai, K. Lakhotia, R. Salakhutdinov, and A. Mohamed, “Hubert: Self-supervised speech representation learning by masked prediction of hidden units,” IEEE ACM Trans. Audio Speech Lang. Process. , vol. 29, pp. 3451–3460, 2021. [Online]. Available: https://doi.org/10.1109/TASLP.2021.3122291
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Y.-A. Chung, Y. Zhang, W. Han, C.-C. Chiu, J. Qin, R. Pang, and Y. Wu, “W2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training,” in 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) . IEEE, 2021, pp. 244–250
2021
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J. Kim, J. Kong, and J. Son, “Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,” in Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event , ser. Proceedings of Machine Learning Research, M. Meila and T. Zhang, Eds., vol. 139. PMLR, 2021, pp. 5530–5540. [Online]. Available: http://proceedings.mlr.press/v139/kim21f.html
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2022
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J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou et al. , “Chain-of-thought prompting elicits reasoning in large language models,” Advances in Neural Information Processing Systems , vol. 35, pp. 24 824–24 837, 2022
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2022
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M. Kim, M. Jeong, B. J. Choi, S. Ahn, J. Y. Lee, and N. S. Kim, “Transfer learning framework for low-resource text-to-speech using a large-scale unlabeled speech corpus,” in Interspeech 2022, 23rd Annual Conference of the International Speech Communication Association, Incheon, Korea, 18-22 September 2022 , H. Ko and J. H. L. Hansen, Eds. ISCA, 2022, pp. 788–792. [Online]. Available: https://doi.org/10.21437/Interspeech.2022-225
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2023
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2023
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2023
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2023
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J. Xue, Y. Deng, F. Wang, Y. Li, Y. Gao, J. Tao, J. Sun, and J. Liang, “M2-ctts: End-to-end multi-scale multi-modal conversational text-to-speech synthesis,” in ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2023, pp. 1–5
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