| Neural speech synthesis with transformer network N Li, S Liu, Y Liu, S Zhao, M Liu Proceedings of the AAAI conference on artificial intelligence 33 (01), 6706-6713, 2019 | 846 | 2019 |
| Neural codec language models are zero-shot text to speech synthesizers C Wang, S Chen, Y Wu, Z Zhang, L Zhou, S Liu, Z Chen, Y Liu, H Wang, ... arXiv preprint arXiv:2301.02111, 2023 | 479 | 2023 |
| Adaspeech: Adaptive text to speech for custom voice M Chen, X Tan, B Li, Y Liu, T Qin, S Zhao, TY Liu arXiv preprint arXiv:2103.00993, 2021 | 176 | 2021 |
| Naturalspeech: End-to-end text-to-speech synthesis with human-level quality X Tan, J Chen, H Liu, J Cong, C Zhang, Y Liu, X Wang, Y Leng, Y Yi, L He, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 167 | 2024 |
| Naturalspeech 2: Latent diffusion models are natural and zero-shot speech and singing synthesizers K Shen, Z Ju, X Tan, Y Liu, Y Leng, L He, T Qin, S Zhao, J Bian arXiv preprint arXiv:2304.09116, 2023 | 150 | 2023 |
| Speak foreign languages with your own voice: Cross-lingual neural codec language modeling Z Zhang, L Zhou, C Wang, S Chen, Y Wu, S Liu, Z Chen, Y Liu, H Wang, ... arXiv preprint arXiv:2303.03926, 2023 | 121 | 2023 |
| Close to human quality TTS with transformer N Li, S Liu, Y Liu, S Zhao, M Liu, M Zhou arXiv preprint arXiv:1809.08895 2, 2018 | 118 | 2018 |
| Developing RNN-T models surpassing high-performance hybrid models with customization capability J Li, R Zhao, Z Meng, Y Liu, W Wei, S Parthasarathy, V Mazalov, Z Wang, ... arXiv preprint arXiv:2007.15188, 2020 | 113 | 2020 |
| Delightfultts: The microsoft speech synthesis system for blizzard challenge 2021 Y Liu, Z Xu, G Wang, K Chen, B Li, X Tan, J Li, L He, S Zhao arXiv preprint arXiv:2110.12612, 2021 | 62 | 2021 |
| Naturalspeech 3: Zero-shot speech synthesis with factorized codec and diffusion models Z Ju, Y Wang, K Shen, X Tan, D Xin, D Yang, Y Liu, Y Leng, K Song, ... arXiv preprint arXiv:2403.03100, 2024 | 58 | 2024 |
| Robutrans: A robust transformer-based text-to-speech model N Li, Y Liu, Y Wu, S Liu, S Zhao, M Liu Proceedings of the AAAI conference on artificial intelligence 34 (05), 8228-8235, 2020 | 46 | 2020 |
| Delightfultts 2: End-to-end speech synthesis with adversarial vector-quantized auto-encoders Y Liu, R Xue, L He, X Tan, S Zhao arXiv preprint arXiv:2207.04646, 2022 | 27 | 2022 |
| Prompttts 2: Describing and generating voices with text prompt Y Leng, Z Guo, K Shen, X Tan, Z Ju, Y Liu, Y Liu, D Yang, L Zhang, ... arXiv preprint arXiv:2309.02285, 2023 | 26 | 2023 |
| Towards contextual spelling correction for customization of end-to-end speech recognition systems X Wang, Y Liu, J Li, V Miljanic, S Zhao, H Khalil IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 3089-3097, 2022 | 24 | 2022 |
| Mixed-phoneme bert: Improving bert with mixed phoneme and sup-phoneme representations for text to speech G Zhang, K Song, X Tan, D Tan, Y Yan, Y Liu, G Wang, W Zhou, T Qin, ... arXiv preprint arXiv:2203.17190, 2022 | 22 | 2022 |
| A light-weight contextual spelling correction model for customizing transducer-based speech recognition systems X Wang, Y Liu, S Zhao, J Li arXiv preprint arXiv:2108.07493, 2021 | 21 | 2021 |
| VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers S Chen, S Liu, L Zhou, Y Liu, X Tan, J Li, S Zhao, Y Qian, F Wei arXiv e-prints, arXiv: 2406.05370, 2024 | 14 | 2024 |
| RetrieverTTS: Modeling decomposed factors for text-based speech insertion D Yin, C Tang, Y Liu, X Wang, Z Zhao, Y Zhao, Z Xiong, S Zhao, C Luo arXiv preprint arXiv:2206.13865, 2022 | 13 | 2022 |
| Foundationtts: Text-to-speech for asr customization with generative language model R Xue, Y Liu, L He, X Tan, L Liu, E Lin, S Zhao arXiv preprint arXiv:2303.02939, 2023 | 9 | 2023 |
| Moboaligner: A neural alignment model for non-autoregressive tts with monotonic boundary search N Li, S Liu, Y Liu, S Zhao, M Liu, M Zhou arXiv preprint arXiv:2005.08528, 2020 | 9 | 2020 |
