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 | 887 | 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 | 551 | 2023 |
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 | 189 | 2024 |
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 | 186 | 2021 |
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 | 179 | 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 | 141 | 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 | 120 | 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 | 114 | 2020 |
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 | 89 | 2024 |
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 | 64 | 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 | 46 | 2020 |
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 | 32 | 2024 |
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 | 31 | 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 | 28 | 2022 |
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 | 23 | 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 |
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 | 14 | 2022 |
Autoregressive Speech Synthesis without Vector Quantization L Meng, L Zhou, S Liu, S Chen, B Han, S Hu, Y Liu, J Li, S Zhao, X Wu, ... arXiv preprint arXiv:2407.08551, 2024 | 11 | 2024 |
E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS SE Eskimez, X Wang, M Thakker, C Li, CH Tsai, Z Xiao, H Yang, Z Zhu, ... arXiv preprint arXiv:2406.18009, 2024 | 10 | 2024 |