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State-of-the-art speech synthesis models try to get as close as possible to the human voice.
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J. Kim, S. Kim, J. Kong, and S. Yoon, “Glow-tts: A generative flow for text-to-speech via monotonic alignment search,” Advances in Neural Information Processing Systems , vol. 33, pp. 8067–8077, 2020
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Y. Zheng, X. Li, F. Xie, and L. Lu, “Improving end-to-end speech synthesis with local recurrent neural network enhanced transformer,” in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020 . IEEE, 2020, pp. 6734–6738. [Online]. Available: https://doi.org/10.1109/ICASSP40776.2020.9054148
T. Li, S. Yang, L. Xue, and L. Xie, “Controllable emotion transfer for end-to-end speech synthesis,” in 2021 12th International Symposium on Chinese Spoken Language Processing (ISCSLP) . IEEE, 2021, pp. 1–5
2021
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K. Lee, “Expressive-fastspeech2,” https://github.com/keonlee9420/Expressive-FastSpeech2 , 2021
2021
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J. Yang, J. Bae, T. Bak, Y. Kim, and H. Cho, “Ganspeech: Adversarial training for high-fidelity multi-speaker speech synthesis,” in Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August - 3 September 2021 , H. Hermansky, H. Cernocký, L. Burget, L. Lamel, O. Scharenborg, and P. Motlícek, Eds. ISCA, 2021, pp. 2202–2206. [Online]. Available: https://doi.org/10.21437/Interspeech.2021-971
2021
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M. Chen, X. Tan, B. Li, Y. Liu, T. Qin, S. Zhao, and T. Liu, “Adaspeech: Adaptive text to speech for custom voice,” in 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 . OpenReview.net, 2021. [Online]. Available: https://openreview.net/forum?id=Drynvt7gg4L
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2020
Cited alongside, same era.
S.-Y. Um, S. Oh, K. Byun, I. Jang, C. Ahn, and H.-G. Kang, “Emotional speech synthesis with rich and granularized control,” in ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2020, pp. 7254–7258
2020
Cited alongside, same era.
J. Yang, J. Lee, Y. Kim, H. Cho, and I. Kim, “Vocgan: A high-fidelity real-time vocoder with a hierarchically-nested adversarial network,” in Interspeech 2020, 21st Annual Conference of the International Speech Communication Association, Virtual Event, Shanghai, China, 25-29 October 2020 , H. Meng, B. Xu, and T. F. Zheng, Eds. ISCA, 2020, pp. 200–204. [Online]. Available: https://doi.org/10.21437/Interspeech.2020-1238
2020
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G. Mittag and S. Möller, “Deep learning based assessment of synthetic speech naturalness,” in Interspeech 2020, 21st Annual Conference of the International Speech Communication Association, Virtual Event, Shanghai, China, 25-29 October 2020 , H. Meng, B. Xu, and T. F. Zheng, Eds. ISCA, 2020, pp. 1748–1752. [Online]. Available: https://doi.org/10.21437/Interspeech.2020-2382
2020
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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 International Conference on Machine Learning . PMLR, 2021, pp. 5530–5540
2021
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V. Popov, I. Vovk, V. Gogoryan, T. Sadekova, and M. Kudinov, “Grad-tts: A diffusion probabilistic model for text-to-speech,” in International Conference on Machine Learning . PMLR, 2021, pp. 8599–8608
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 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 . OpenReview.net, 2021. [Online]. Available: https://openreview.net/forum?id=piLPYqxtWuA
2021
Cited alongside, same era.
X. Cai, D. Dai, Z. Wu, X. Li, J. Li, and H. Meng, “Emotion controllable speech synthesis using emotion-unlabeled dataset with the assistance of cross-domain speech emotion recognition,” in ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2021, pp. 5734–5738
2021
Cited alongside, same era.
2021
Later among the works it cites.
2022
Later among the works it cites.
2022
Later among the works it cites.
Y. Wu, X. Tan, B. Li, L. He, S. Zhao, R. Song, T. Qin, and T. Liu, “Adaspeech 4: Adaptive text to speech in zero-shot scenarios,” 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. 2568–2572. [Online]. Available: https://doi.org/10.21437/Interspeech.2022-901
2022
Later among the works it cites.
K. Zhou, B. Sisman, R. Liu, and H. Li, “Emotional voice conversion: Theory, databases and esd,” Speech Communication , vol. 137, pp. 1–18, 2022
2022
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T. Kaneko, K. Tanaka, H. Kameoka, and S. Seki, “istftnet: Fast and lightweight mel-spectrogram vocoder incorporating inverse short-time fourier transform,” in ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2022, pp. 6207–6211
2022
Later among the works it cites.
Y. Guo, C. Du, X. Chen, and K. Yu, “Emodiff: Intensity controllable emotional text-to-speech with soft-label guidance,” in ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2023, pp. 1–5
2023
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