Yanqing Liu
Cited by
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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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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