| 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 | 680 | 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 | 140 | 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 | 130 | 2021 |
| Close to human quality TTS with transformer N Li, S Liu, Y Liu, S Zhao, M Liu, M Zhou arXiv preprint arXiv:1809.08895, 2018 | 109 | 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 | 89 | 2020 |
| 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, ... arXiv preprint arXiv:2205.04421, 2022 | 80 | 2022 |
| 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 | 47 | 2021 |
| 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 | 34 | 2020 |
| 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 | 29 | 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 | 26 | 2023 |
| 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 | 18 | 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 | 16 | 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 | 12 | 2021 |
| 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 |
| 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 | 8 | 2022 |
| 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 | 6 | 2022 |
| FoundationTTS: Text-to-Speech for ASR Custmization with Generative Language Model R Xue, Y Liu, L He, X Tan, L Liu, E Lin, S Zhao arXiv preprint arXiv:2303.02939, 2023 | 4 | 2023 |
| 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 | 2 | 2023 |
| Improving Contextual Spelling Correction by External Acoustics Attention and Semantic Aware Data Augmentation X Wang, Y Liu, J Li, S Zhao ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 1 | 2023 |
| Enhancing Monotonicity for Robust Autoregressive Transformer TTS. X Liang, Z Wu, R Li, Y Liu, S Zhao, H Meng INTERSPEECH, 3181-3185, 2020 | | 2020 |
