Follow
Yanqing Liu
Title
Cited by
Cited by
Year
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
6802019
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
1402023
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
1302021
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
1092018
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
892020
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
802022
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
472021
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
342020
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
292023
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
262023
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
182022
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
162022
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
122021
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
92020
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
82022
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
62022
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
42023
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
22023
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
12023
Enhancing Monotonicity for Robust Autoregressive Transformer TTS.
X Liang, Z Wu, R Li, Y Liu, S Zhao, H Meng
INTERSPEECH, 3181-3185, 2020
2020
The system can't perform the operation now. Try again later.
Articles 1–20